Saurav Patro Contact me
Saurav Patro · Product leader · Dubai, open to relocation

I'm Saurav. I build products people come back to.

Founder. Chief of staff to a CEO. Product leader at Zomato, Amazon and Careem. Over ten years building for tens of millions of customers across India and the Middle East.

[email protected] · · LinkedIn ↗

Where I've worked, and my biggest number at each
  • Careem2024 to now5% at +70%of Careem Food orders now scheduled, at 70% higher order value
  • Zealth2023First 5companies in India's ABHA sandbox
  • Hike2022$100Mrecurring revenue, profitable day one
  • Amazon2020$130Mincremental seller revenue
  • Zomato2018−20% → +16%EBITDA, 250-city P&L
  • Travel Triangle201790%of repeat travellers via weekend getaways
  • Delhivery2015$3Munrealised revenue recovered
  • Bharti Airtel2012First jobsales and distribution

MBA projects with Pulsar Products (USA), Mary Kay (China) and Tata Tinplate (India).

  1. Give me a goal, not a spec.A broad problem comes back as a portfolio that ships.
  2. Every side wants to stay.Customers, sellers, riders and partners.
  3. I build it before I pitch it.Prototypes on Claude Code, Lovable and Replit.
  4. Teams of 3 to 230.Seven direct reports today; my first intern is now a design manager.
Where I've built

Seven companies. Every side of the market.

Founder, early employee, chief of staff and product leader, across logistics, travel, food delivery, e-commerce, gaming, health and a super-app.

For recruiters and hiring managers

What are you hiring for?

Pick the closest fit. The headline, the evidence and the order of the case studies change to match.

Roles that own a marketplace, partner platform or contributor network: onboarding and listing, payouts and incentives, trust and quality on both sides.

  • Onboard and list partners at scaleTenants: 20+ partners in Dubai, 15 in Jordan, 7 in Egypt within six months, with vetting and agreed commercials as the gate to listing.
  • Grow both sides of the marketCareem went from ~5% to ~96% of a car-rental partner's GTV; customers who adopted a partner service tripled their app spend.
  • Pay and motivate a distributed workforceZomato payouts rebuilt in six phases, ending with rate cards for rider cohorts as small as 10; a 90K-cyclist fleet built from zero.
  • Keep quality high as supply scalesKarma Score fraud system cut abuse 90% at Zomato; a 30-signal quality engine cut returns 25% at Amazon.
  • Bring many parties onto one platformZealth: government, insurers, hospital chains, labs and clinics on one consent-based record.

Roles that take AI from demo to daily use: choosing the problem, proving it against a baseline, rolling it out safely and measuring adoption.

  • Ship an LLM product with real adoptionAI grocery list: 22% week-one adoption against a 5 to 7% target, 65% of adopters repeating within two weeks.
  • Evaluate before you scaleVersion one ran on human transcribers, so the model had a baseline to beat; Ask Careem was tested on a shadow replica of production and reached ~98% accuracy.
  • Take AI across a whole companyUp to 80% of Careem's commercial and operations workflows now run through AI; merchant onboarding cut from 6 days to 1.
  • Build it yourselfPrototypes on Claude Code, Lovable and Replit, including the one that won the grocery list form-factor debate. See what I've built.

Roles that sit with a client or a business unit and deliver change: AI transformation, forward-deployed product work, strategy that ends in something running.

  • Run AI transformation inside a companyAI Enablement began as three people and became the implementation partner for every Careem vertical; up to 80% of commercial and operations workflows now run through AI.
  • Find the right problem, not the easy oneI set up Careem's company-wide AI hackathon so every vertical surfaced its top problems, then took the goal they had all declined: raising grocery basket size.
  • Prove it before you scale itThe grocery list ran on human transcribers first, so the model had a baseline to beat; a fake door validated Careem for Business in two weeks.
  • Turn a P&L aroundA 250-city P&L moved from -20% to +16% EBITDA at Zomato.
  • Work at the CEO's sideAs Chief of Staff to the CEO at Hike, led a 230-person team through the pivot from messaging to gaming.

Roles that own acquisition, activation, conversion and revenue: freemium to paid, pricing and fees, experiments that decide what ships.

  • Convert free users to paidHike: a pay-to-play loop converting 8% of new users to paid each month; VIP tiers raised spend 30% and D30 retention from 12% to 30%.
  • Own revenue, not just features$100M in recurring revenue at Hike, profitable from day one; $130M incremental seller revenue at Amazon.
  • Price and monetiseDynamic pricing improved margins 18% and a targetable platform-fee structure shipped at Zomato.
  • Test demand before buildingCareem for Business: a fake-door page drew 200+ interest forms from ~70 companies in two weeks.
  • Cut friction from the funnelThe grocery list took a 40-click weekly shop to about 3 clicks.

Roles that own the consumer experience, loyalty and retention: why people come back, and what they're rewarded with when they do.

  • Build repeat into a rare purchaseTravel Triangle: referral and loyalty rewards; weekend getaways drew 90% of repeat travellers and 40% of revenue within six months.
  • Design tiers people climbHike VIP tiers raised spend 30% and D30 retention from 12% to 30%.
  • Use trust to lift conversionTop Brands at Amazon: D2C brand revenue +200% at 3% higher conversion.
  • Make a habit stickAI grocery list: 65% of adopters repeated within two weeks. AI Meals on Careem Food: ~60% three-day repeat against a 40% target, gross profit per user +8%.

Roles in e-commerce, food delivery and quick commerce: selection, sellers, fulfilment speed and unit economics.

  • Make food ordering a habitAI Meals on Careem Food: one-tap set meals from nearby favourites; ~60% three-day repeat against a 40% target, and gross profit per user +8% even as order value fell.
  • Grow basket sizeAdopters of the grocery list went from ~70 to ~250 AED per order; I refused a big-basket discount and used country-of-origin tags to anchor quality.
  • Grow the seller baseMobile-first onboarding for the micro-sellers behind 80% of India volume at Amazon: $130M incremental revenue.
  • Make delivery faster and cheaperZomato: cyclists took 43% of orders at 50% lower cost; cost per order ~₹120 to ~₹78.
  • Fix unit economicsA 250-city P&L moved from -20% to +16% EBITDA at Zomato.

Roles in health tech, wearables and consumer apps: privacy and consent, daily habits, and partners in the care system.

  • Build on sensitive health dataZealth, as co-founder and CPO: a consent-based health-records layer where patients grant time-limited access, one of the first five companies in India's ABHA sandbox.
  • Bring the care system on boardGovernment, insurers, hospital chains, diagnostic labs and private clinics; the pilot ran across 8 hospitals and 40 clinics and earned revenue.
  • Design privacy into the productCubby, a baby-care app I built myself, with per-baby access controls and an audit step when family members are added. See what I've built.
  • Make a daily habit stickD30 retention from 12% to 30% at Hike; 65% of grocery list adopters repeated within two weeks.

Roles where the product runs on fleets, devices, networks or deliveries: operations at scale, safety, and rollout across many markets.

  • Build and run a fleetZomato: a 90K-cyclist fleet from zero, carrying 43% of orders at 50% lower cost, on a rebuilt assignment engine.
  • Design for safety, not just speedGuardrails for women riders and riders with disabilities, and the first delivery-partner insurance at Zomato.
  • Scale across cities and countriesZomato grew from 5 to 500 cities during my time; Tenants launched across the UAE, Jordan and Egypt.
  • Fix the logistics layerAmong Delhivery's first 30 employees; built AddFix, an address-resolution engine later offered to Amazon as a service.
  • Mobility platformsCar rental, e-bikes and home services on Careem through Tenants, with Careem now driving ~96% of the car-rental partner's GTV.

Roles in consumer fintech, payments and spend management: wallets, subscriptions, payouts and expenses that people actually enjoy using.

  • Spend managementCareem for Business: per-service spend policies, daily-expiring allowances, an admin workspace and a company-funded wallet; $200K a month three months after launch.
  • Consumer subscriptionsCareem Plus: rebuilt onboarding, cross-sell and upsell; trial-to-paid 40% to 70%, retention 40% to 65%.
  • Wallets and stored valueDMiles prepaid wallet: $3M recovered, leakage -95%. A closed corporate wallet on Careem Pay rails.
  • Virtual economies and cryptoHike: a two-currency economy and a pay-to-play loop converting 8% of new users to paid each month; a Web3 format among the five piloted.
  • PayoutsRider payouts at Zomato, rebuilt with finance in six phases down to cohort rate cards.
  • Redesigns that moved the numberMobile-first seller onboarding at Amazon ($130M incremental revenue); the Careem Plus rebuild; the grocery revamp.

Head of, VP and executive roles: owning a P&L, setting the bar for a product org, and staying hands-on while doing it.

  • Own a P&LA 250-city P&L at Zomato from -20% to +16% EBITDA on a $20M budget.
  • Run the company beside the CEOChief of Staff to the CEO at Hike: led 230 people through the pivot in six months to $100M recurring revenue, reporting to the CEO, board and investors.
  • Build teams and grow peopleSeven direct reports today (five PMs, two APMs). AI Enablement grew from three people into Careem's central AI function; the intern on that first team is now a design manager.
  • Lead design without owning itDesign and engineering work to my charter on a dotted line; I win debates with working prototypes, and rebuilt the merchant platform around four personas.
  • Set direction across a companyA company-wide AI hackathon every vertical fed its top problems into; up to 80% of commercial and operations workflows now run through AI.
Selected work

How the work actually worked

Three cases to start, closest to your role if you picked one. Open any for the problem, the decision, the mechanism and the result.

Order for Change role type

All twelve case studies, newest first.

Careem · 2024MarketplacePartner platform

Tenants: a partner platform where partners grow with us

Open caseClose

Careem had payments, discovery, a user funnel and advertising. It did not have fulfilment for the long tail of services people want. Tenants let local businesses plug into everything else.

20+ / 15 / 7 partners in Dubai, Jordan, Egypt in 6 monthscar-rental partner GTV via Careem ~5% to ~96%home-services partner ~92%adopters 3x app spendCareem's first equity stake in a partner app
Situation

Careem had payments, discovery, a user funnel and advertising, but no fulfilment for the long tail of services people want. Building every vertical in-house (car rental, laundry, home cleaning, pet grooming, gardening, e-bikes) would never pay back. Car rental ran through Swapp, a partnership live since 2022 that had become strained.

Task

Bring the long tail onto Careem without funding new verticals, and turn the Swapp partnership around.

Action
  • Opened the platform: any provider vetted by Careem and agreed on commercials could sell through it, with fulfilment staying with the partner.
  • Partners plug into Careem Pay, discovery, the design system and the existing customer funnel.
  • Rolled out market by market: Dubai, then Jordan, then Egypt.
  • Took over Swapp, rebuilt the joint roadmap within six months, proved the new model with a proof of concept, then closed an exclusivity deal with equity for Careem (announced in 2025).
  • Built lasting partnerships with Justlife in home services (announced by Careem) and Washmen in laundry.
Result
  • 20+ partners in Dubai, 15 in Jordan, 7 in Egypt within six months
  • Car-rental partner GTV via Careem ~5% to ~96%
  • Home-services partner ~92% of GTV via Careem
  • 45%+ of adopters tripled their app spend
  • Careem's first equity stake in a partner app
Careem · 2025Zero to oneB2B billing

Careem for Business: adding companies as a paying side

Open caseClose

Support tickets in the last five days of every month were dominated by one request: tax invoices. The people asking were being reimbursed by employers. So the employer became the customer.

200+ interest forms from ~70 companies in 2 weeks$200K/month revenue three months after launchnorth star: new accounts
Situation

While I ran a six-month care-automation strategy, agent-only tickets rose from about 10% on a normal day to about 70% in the last five days of each month, in the UAE, KSA and Jordan alike. The cause was tax-invoice requests: Careem issued receipts, not tax invoices. Interviews with 15+ users found employers reimbursing 20 to 40 trips and orders a month; real-estate agents were the surprising segment.

Task

The idea had been shelved before. Prove that companies would pay, then make them a paying side, while still delivering the care-automation goals.

Action
  • A fake-door page I built on Lovable, shown through a small checkout banner only to the cohorts asking for invoices.
  • Funded through a proposal to Careem's leadership about a month after the pattern appeared.
  • Built an admin workspace with per-service spend policies, a company-funded wallet with allowances that expire daily, and a “pay as business” toggle at checkout.
  • Launched lean on a Lovable site, an ops dashboard and spreadsheets, and sold the first accounts myself.
  • Build, operate, transfer: after its first sales rep, it moved to the commercial org.
Result
  • 200+ interest forms from ~70 companies in two weeks
  • $200K a month three months after launch
  • North star: new business accounts; revenue treated as the output
  • Grew beyond the UAE and KSA into Jordan and Egypt, now with its own sales, invoicing and compliance team
Careem · 2025LLM product

AI grocery list: from a 40-click shop to 3

Open caseClose

Photograph a list, paste one forwarded on WhatsApp, or speak to an agent. Version one ran on human transcribers, so the model had a baseline to beat before it shipped.

22% week-one adoption vs 5-7% target65% repeat within 2 weeksadopter basket ~70 to ~250 AED
Situation

Quick commerce trains people to top up, not stock up, and a weekly shop took about 40 clicks. Raising grocery order value was the one goal every vertical declined at the company hackathon I created.

Task

My team took that goal: raise order value without buying it with discounts.

Action
  • Evaluated about six form factors and chose a single-page list on a cognitive-load argument; won the internal debate with a prototype I built myself.
  • Version one ran on human transcribers; the LLM replaced them only after matching that baseline.
  • Shipped image input first and deferred voice, because conversational input cost more per interaction at the time.
  • Refused a big-basket discount and used country-of-origin tags to anchor quality instead.
  • Showed out-of-stock items up front with a “back in stock tomorrow” tag, to protect trust.
Result
  • Weekly shop from ~40 clicks to ~3
  • 22% week-one adoption against a 5 to 7% target; 25 to 30% sustained
  • 65% of adopters repeated within two weeks
  • Adopter order value ~70 to ~250 AED
  • A falsified hypothesis became a second product, “people also buy”; Uber and noon shipped equivalents within about two months
Careem · FoodPersonalisationHabit loop

AI Meals: a complete meal in one tap

Open caseClose

Food discovery leaked at every step, and office-goers kept ordering from the same handful of restaurants. So we built for habit instead of basket size: complete set meals from nearby favourites, checked out in one tap.

~60% three-day repeat vs a 40% targetgross profit per user +8%more conversion to Careem Plus
Situation

Food discovery leaked at every step: about 30% of users lost from search to cuisine, 50% from cuisine to restaurant and 40% from menu to checkout. Most office-goers, many of them expats who don't cook, ordered from the same 10 to 12 restaurants near where they live or work.

Task

Build for repeat and habit instead of basket size, against a 40% three-day-repeat target set before launch, and bring two teams with order-value targets along.

Action
  • A carousel of complete set menus for each user, drawn from different restaurants.
  • A location layer: restaurants popular in your building surface their best sellers for you.
  • Single-tap checkout, “buy now” instead of “add to cart”.
  • Aligned the two teams with a working prototype and a committed repeat target.
  • Piloted in Abu Dhabi only and left Dubai untouched until repeat was proven.
Result
  • ~60% three-day repeat against a 40% target (users ordering 10+ times a month)
  • Gross profit per user +8% while order value fell, as planned
  • Higher conversion to Careem Plus
Careem · 2024 to nowLLM toolingSkills marketplace

AI Enablement: Ask Careem, merchant tooling and a published skill

Open caseClose

A charter that started as three people and became the implementation partner for every vertical, now building on Claude Code.

~98% Ask Careem accuracyup to 80% of ops workflows on AImerchant onboarding 6 days to 1merchant revenue +24%
Situation

Process knowledge sat across Confluence, Notion and Drive, restaurant onboarding took six days, and every Careem vertical needed design, engineering, PRD and data help to put AI to work.

Task

Pitch and found an AI Enablement charter, starting as three people, and make AI part of how work gets done across the company.

Action
  • Created a company-wide hackathon where each vertical submitted its own top problems against the company's goals, so priorities came from the businesses.
  • Ask Careem: a retrieval assistant in Slack over Confluence, Notion and Drive that raises Jira tickets and runs workflows in one click, tested on a shadow replica of production before launch.
  • Rebuilt the merchant platform after benchmarking Keeta and DoorDash, for owners, managers, restaurant staff and kitchen staff, with AI menu ranking, image checks, dish classification and dynamic pricing.
  • Built an analysis skill (cross-analysis, dependencies, leakage detection), published on Careem's internal skill marketplace.
  • Moved the team's tooling from ChatGPT to Gemini to Claude Code.
Result
  • Ask Careem ~98% accuracy after rollout
  • Up to 80% of commercial and operations workflows run through AI
  • Merchant onboarding 6 days to 1
  • Merchant revenue +24%
  • Three people became Careem's central AI and platform function
Zealth · 2023Zero to onePartnershipsPartner side of a platform

Zealth: health records on government rails

Open caseClose

As co-founder and CPO, I built a consent-based health-records layer on India's ABHA rails, the way payment apps sit on UPI. It only worked if five partner groups took part: the government, insurers, hospital chains, diagnostic labs and private clinics.

one of the first 5 companies in the ABHA sandbox5 partner groups8 hospitals and 40 clinics piloted
Situation

Patients in India carried paper files between hospitals that would not accept each other's reports, so tests were repeated and no doctor saw the full history.

Task

As co-founder and CPO, build a consent-based health-records layer on India's ABHA rails, the way payment apps sit on UPI, and bring every side of care onto it.

Action
  • Normalised imaging, pathology and lab reports into one longitudinal record, shared per doctor through time-limited consent.
  • A patient app, plus a patient-history and outreach tool for doctors and labs.
  • Brought five partner groups on: government, insurers, hospital chains, diagnostic labs and private clinics.
  • Stayed a neutral layer, not a provider, payer or insurer.
  • When the government deprioritised ABHA, shut Zealth down rather than spend limited capital waiting.
Result
  • One of the first 5 companies in the national ABHA sandbox
  • Pilot across 8 hospitals and 40 clinics
  • Doctors and labs adopted it, and the pilot earned revenue
  • Lesson: a platform on someone else's rails needs a plan for when those rails move
Hike · 2022Economy design

A two-currency game economy, profitable from day one

Open caseClose

As Chief of Staff to the CEO, I ran the pivot from messaging to gaming and the economy that paid for it.

$100M recurring revenue8% of new users paid monthlyVIP spend +30%D30 retention 12% to 30%
Situation

Hike was pivoting from messaging to gaming and needed an economy that paid for the move.

Task

As VP and Chief of Staff to the CEO, run the company internally, lead the pivot and own the game economy.

Action
  • Piloted five formats against each other (web3, non-web3, cash, non-cash, freemium) before committing; Hike's strengths in matching, relays and concurrency pointed to player-versus-player hyper-casual games.
  • Kept web3 mechanics (collect, upgrade and morph pawns) and dropped the web3 cost, because players did not care about owning NFTs.
  • Ran Rush's two-currency economy and built the pay-to-play loop for the freemium tier.
  • Designed Rush VIP tiers.
  • Set up Hike's first Data and Revenue team; A/B testing and pricing governance became the default path to ship.
Result
  • 230-person team through the pivot in 6 months
  • $100M recurring revenue, profitable from day one
  • 8% of new users converted to paid every month
  • VIP spend +30%; D30 retention 12% to 30%
  • Margins +20%
Amazon · 2020Seller sideTrust

Making a micro-seller's first 100 orders succeed

Open caseClose

I visited micro-merchants in their stores. The new ones were lost, and many went to cyber cafes to use a web-first seller portal. So we rebuilt it mobile-first, from India for the world.

$130M incremental revenueTop Brands: D2C revenue +200%returns -25%
Situation

Micro-sellers were behind 80% of India volume, and many went to cyber cafes because the seller portal was web-first. Buyers could not tell real D2C brands from fakes, and fraudulent sellers reached customers.

Task

As single-threaded owner of seller success, double onboarding success, measured on a seller's first 100 orders.

Action
  • Redesigned seller onboarding mobile-first, with gamification, later scaled globally.
  • Top Brands: a product-page trust signal (buyers this month, positive reviews, return rate), built after counterfeit and bad-seller detection work.
  • A quality engine on 30+ signals that blocked fraudulent sellers and listings.
  • Founding team of India Ultrafast Fresh: unified inventory across warehouses.
Result
  • $130M incremental revenue
  • D2C brand revenue +200% at 3% higher conversion
  • Returns -25%
  • Ultrafast Fresh: daily orders +20%, fulfilment cost -10%
Zomato · 2018Marketplace engineSupply design

The fulfilment engine: less money, more partners

Open caseClose

The north star was "shutdown", the time the app showed nothing deliverable, and the goal was zero. Paying more bought only marginal supply. Unlocking new supply changed the curve.

90K cyclist fleet from zero43% of orders at 50% lower costcost per order ~₹120 to ~₹78
Situation

80 to 85% of peak orders were within about 3 km, but serviceability rules switched off long-distance restaurants at peak, and requiring a motorcycle filtered out supply. Milk and newspaper riders on cycles sat idle at lunch and dinner. Paying more bought only marginal supply.

Task

Drive “shutdown”, the time the app showed nothing deliverable, to zero, at a cost per order that pays.

Action
  • Weighed higher incentives, surge pricing and restaurant self-delivery, and chose new supply.
  • Sent short trips to cyclists; piloted in Delhi, Gurgaon, Noida and Hyderabad, then rolled out nationally.
  • Rebuilt order assignment to be multimodal, and partner profiles that had assumed a licence and vehicle.
  • Introduced delivery-partner insurance, and guardrails: no night orders for women riders, no multi-floor buildings for riders with disabilities.
  • Kept the cyclist-or-biker choice hidden from customers (ETAs differed by only 30 to 45 seconds) and made assignment concentric.
Result
  • 90K cyclists from zero
  • 43% of orders at 50% lower cost
  • Cost per order ~₹120 to ~₹78
  • Zomato's first delivery-partner insurance
Zomato · 2019IncentivesPayouts & fees

Rider rate cards, offer stacking and the fee platform

Open caseClose

One payout structure per city could not pay a two-hour cyclist and a twelve-hour biker fairly. We rebuilt payouts in six phases, down to rate cards for cohorts as small as 10 riders.

250-city P&L -20% to +16% EBITDAplatform abuse -90%dynamic pricing margin +18%
Situation

One payout structure per city could not pay a two-hour cyclist and a twelve-hour biker fairly. Customers had to do the maths across bank, wallet, partner and Gold offers, and abuse ate into margin, all while Zomato grew from 5 to 500 cities.

Task

Lead the fulfilment product pod (assignment, serviceability, payouts, fraud and cash collection) and own the unit economics of a 250-city P&L on a $20M budget.

Action
  • Rebuilt rider payouts with the finance org in six phases: multimodal payouts, incentive tiers by partner type, then cohort-level and part-time rate cards.
  • Built Zomato's first promotion platform: offers stacked automatically in one cart with one total.
  • Set a platform-fee structure that could be added, removed and targeted by cohort.
  • Deployed the Karma Score ML fraud system and a dynamic pricing engine.
Result
  • 250-city P&L -20% to +16% EBITDA
  • Platform abuse -90%
  • Margins +18% from dynamic pricing
  • Rate cards for cohorts as small as 10 riders; riders engaged more, earned more and stayed longer
Travel Triangle · 2017Three-sided marketplaceReferral & loyalty

Turning a once-in-a-lifetime trip into a repeat business

Open caseClose

Honeymoons to island destinations: high ticket, very high acquisition cost, and about 5% repeat over nearly five years. One purchase could not pay for the customer who made it.

weekend getaways: 90% of repeat travellers, 40% of revenue in 6 monthslead-to-conversion +23%
Situation

Honeymoons to island destinations: high ticket, very high acquisition cost, and about 5% repeat over nearly five years. One purchase could not pay for the customer who made it.

Task

As Product Leader, Customer Experience, own the experience across travellers, local travel agents and on-ground providers, and make travellers come back.

Action
  • Structured all customer feedback by agent, location and itinerary, to nudge travellers before known on-ground problems and set expectations where nothing could be fixed.
  • Built referral and loyalty rewards, with trips per converted traveller as the north star.
  • Launched weekend getaways near Mumbai, Pune, Bengaluru and Delhi: a reason to come back every year, and a place to redeem points.
  • A retargeting and lead-scoring engine on 25+ profile attributes, with a 40-person CX team.
Result
  • Weekend getaways: 90% of repeat travellers and 40% of revenue within six months
  • One conversion led to about 20 trip conversions
  • Lead-to-conversion +23%
  • 8,000+ people sent on offbeat trips such as Rishikesh
Delhivery · 2016B2B billing

DMiles: a prepaid wallet for risky shippers, and AddFix

Open caseClose

Small e-commerce sites would launch, sell through short-form content and close within three or four months, which was exactly the credit line logistics extended.

$3M unrealised revenue recoveredleakage -95%
Situation

Small e-commerce sites would launch, sell through short-form content and close within three or four months, exactly the credit line logistics extended. And Indian addresses are free text, so one door arrives written many ways.

Task

As one of Delhivery's first 30 employees, stop the credit leakage and make addresses routable.

Action
  • DMiles: new long-tail shippers moved to prepaid-only through a closed B2B wallet until they reached a set number of orders.
  • AddFix: clustered variants of the same address by learning from successful deliveries, alternates and shared markers, giving routing and capacity planning a structured location.
Result
  • $3M unrealised revenue recovered
  • Leakage -95%
  • AddFix later offered to Amazon as a service
Applying for

Product Manager, Claude Marketplace

The role, line by line, against the work above.

Every side of the table

I've been the platform (Careem), the seller side (Amazon), the operator paying supply (Zomato) and the matchmaker between three sides (Travel Triangle). Partners and buyers are both people I've built for.

The money plumbing

Prepaid B2B wallets, rider payouts, company spend policies, offer stacking and platform fees. A marketplace is only as trusted as its ledger.

A Claude builder

I ship with Claude Code, publish skills, and built this site, my last fake-door pages and several products end to end myself. I would be a Marketplace partner's PM and its customer at once.

  • Mar 2026Launched in limited preview: enterprises apply part of an existing Anthropic commitment to Claude-powered partner tools, and Anthropic manages invoicing for partner spend. claude.com/marketplace
  • Sep 2026Opened more widely, reported with 2,000+ plugins and connectors plus partner agents and products. BleepingComputer
The role asks forWhere I've done it
Own the marketplace end to end, onboarding and listing through purchase and billingTenants (vetting, commercials, listing on shared rails) and Careem for Business (admin workspace, funded wallet, checkout toggle)
Commercial workflows that meet finance, audit and compliance needsDMiles prepaid B2B wallet, Zomato payouts built with the finance org, company spend policies at Careem
Commercial incentives built into the productCohort rate cards at Zomato, the referral loop at Travel Triangle, the Hike economy
Built with or shipped on LLMsAI grocery list, Ask Careem, a skill published on Careem's internal skill marketplace
Go-to-market and partner dealsSwapp exclusivity and equity deal at Tenants; selling with and to enterprises at Careem, Amazon and Delhivery
Partner, app store or ecosystem experiencePlatform side at Careem, seller side at Amazon, operator side at Zomato
Zero to oneTenants, Careem for Business, the Hike pivot, Zealth
Define success metrics"Shutdown at zero" at Zomato, trips per converted traveller at Travel Triangle, new accounts at Careem for Business

Partner success

What share of a partner's new enterprise revenue does the Marketplace source, and is that share growing?Measured before: Tenants partner GTV, ~5% to ~96%.

Commitment drawdown

When committed spend goes to a partner, both finance teams need the same record of what was drawn, against which contract, and when. The ledger is part of the product.Built before: DMiles and the Careem for Business wallet.

Listing to purchase

How long from a partner submitting to an enterprise buying through procurement, and which step loses the most partners?Cut before: merchant onboarding, 6 days to 1.

Incentives by cohort

A partner program with one set of terms will fit the median partner and nobody else. Which cohorts need their own terms?Built before: Zomato rate cards for cohorts as small as 10 riders.

These are questions, not claims about how the Marketplace works today. Facts about it come from the linked public sources.

Contact

Contact me with your interest

Tell me about the role, or better, the problem everyone around you has written off. Based in Dubai, open to relocation.

Go deeper

Everything else, if you want to check.

Nothing here is needed to understand the work above. Open whatever you want to verify.

Ask about my workType a question. Every answer names the case or record entry it comes from.
Ask the record

Ask about my work

Searches the case studies on this page. Every answer names where it comes from.

The full record59 things delivered, by company, each with its number.
The full record

Everything I've delivered, documented.

Every item from my CVs and interviews in one place, 59 entries in all. The sections above tell the best stories; this is the complete list, and the Ask box searches all of it.

Careem 2024 to now

  • Tenants partner platform

    Situation
    Building every service vertical in-house would never pay back, and Careem had no fulfilment for the long tail of services.
    Task
    Bring the long tail onto Careem without funding new verticals.
    Action
    Vetted third-party businesses plug into Careem Pay, discovery, the design system and the customer funnel; fulfilment stays with the partner, and agreed commercials gate listing.
    Read the case study
    Result
    • 20+ partners in Dubai, 15 in Jordan, 7 in Egypt in six months
    • Partner GTV via Careem ~5% to ~96% (car rental), ~92% (home services)
    • 45%+ of adopters tripled their app spend
  • Swapp partnership turnaround

    Situation
    Swapp had powered car rental on Careem since 2022, but the partnership was strained.
    Task
    Take it over and turn it around.
    Action
    Rebuilt the joint roadmap within six months, proved the new model with a proof of concept, then closed an exclusivity deal.
    Read the case study
    Result
    • Exclusivity, with equity in Swapp for Careem: its first stake in a partner app
    • Careem now drives ~96% of the partner's GTV
  • Justlife and Washmen partnerships

    Situation
    Home services and laundry needed fulfilment Careem did not run itself.
    Task
    Bring long-term partners onto Tenants and grow them with the platform.
    Action
    Onboarded Justlife in home services and Washmen in laundry onto Tenants.
    Read the case study
    Result
    • Home-services partner: ~92% of its GTV via Careem
  • Careem for Business: the discovery

    Situation
    Agent-only tickets rose from about 10% on a normal day to about 70% in the last five days of each month.
    Task
    Find out why, while running a six-month care-automation strategy.
    Action
    Traced the spike to tax-invoice requests (Careem issued receipts, not tax invoices) and interviewed at least 15 users across three markets: employers were reimbursing 20 to 40 trips and orders a month, and real-estate agents were the surprising segment.
    Read the case study
    Result
    • Same pattern across UAE, KSA and Jordan
    • Became the case for Careem for Business
  • Careem for Business: fake-door validation

    Situation
    The idea had been shelved before, so demand had to be proven first.
    Task
    Prove companies would pay before building the product.
    Action
    A fake-door site built on Lovable and shown through a small checkout banner only to the cohorts that had asked for invoices. Unexpected demand surfaced for intra-city document and parcel delivery, which companies were doing by booking taxis.
    Read the case study
    Result
    • 200+ interest forms from ~70 companies in two weeks
    • Most companies 100 to 400 staff, with a tail from 50 to 10,000
    • Typically only 20 to 30 employees per company already on Careem
  • Careem for Business: the product

    Situation
    Employees were paying for trips and orders, then claiming them back from employers.
    Task
    Make the company the paying customer, funded without pausing care automation.
    Action
    A company-funded closed wallet on Careem Pay rails with daily allowances that expire at end of day, per-service spend policies, an admin web portal, and pay-as-business at checkout. Funded through a proposal to Careem's leadership team about a month after the pattern appeared.
    Read the case study
    Result
    • $200K a month three months after launch
    • North star: new business accounts; revenue treated as an output
    • First accounts sold personally
  • Careem Plus membership

    Situation
    Trial-to-paid sat at 40% and retention at 40%.
    Task
    Own the paid membership programme end to end and lift both.
    Action
    Rebuilt onboarding, cross-sell and upsell.
    Result
    • Trial-to-paid 40% to 70%
    • Retention 40% to 65%
  • AI Meals on Careem Food

    Situation
    Food discovery leaked at every step, and office-goers reordered from the same 10 to 12 restaurants.
    Task
    Build for repeat and habit, not basket size, against a target set before launch.
    Action
    Complete set meals from nearby favourites with one-tap checkout, plus a location layer surfacing what is popular in your building. Piloted in Abu Dhabi only, with a target set before launch.
    Read the case study
    Result
    • ~60% three-day repeat vs a 40% target (users ordering 10+ times a month)
    • Gross profit per user +8% while order value fell
    • Higher conversion to Careem Plus
  • Scheduled orders on Careem Food

    Scheduled orders on Careem Food, so customers can order ahead.

    Result
    • 5% of Careem Food orders
    • 70% higher order value than the average order
  • AI grocery list

    Situation
    Quick commerce trains people to top up, and a weekly shop took about 40 clicks.
    Task
    Raise grocery order value, the goal every vertical declined at the hackathon.
    Action
    Photograph a list, paste one forwarded on WhatsApp, or speak to an agent; matched against purchase history and inventory into a single-page basket. Version one ran on human transcribers as the baseline the model had to beat. Image input first, voice later, sequenced on cost.
    Read the case study
    Result
    • 40-click weekly shop to about 3
    • 22% week-one adoption vs a 5 to 7% target; 25 to 30% sustained
    • 65% of adopters repeat within two weeks
    • Adopter order value ~70 to ~250 AED
    • Uber and noon shipped equivalents within about two months
  • Grocery revamp, five workstreams

    Situation
    Customers assumed quick commerce cost more than local retail, and fresh produce needed a quality pivot.
    Task
    Run five research-led workstreams in parallel.
    Action
    A research-led programme run in parallel: order-volume uplift, price perception (quick commerce is not more expensive than local retail), a fresh-produce quality pivot, country-of-origin tags on SKUs, and a full design overhaul. The shopping list was the hardest to get approved because it was new to the market.
    Read the case study
    Result
    • Refused a big-basket discount; country-of-origin tags anchored quality instead
  • Hypermarket research method

    Situation
    The team needed to know how big-basket shoppers actually plan a trip.
    Task
    Find the cohort a shopping-list product would serve.
    Action
    In-person intercepts inside hypermarkets with shoppers above a spend threshold, asking how they prepared for the trip rather than what they bought, with live price comparisons.
    Read the case study
    Result
    • Found a sub-1% cohort already building week-long carts by hand
    • Packaging waste surfaced as an unexpected motivation
    • Saturation after the sixth or seventh user
  • People also buy

    Situation
    Users finished their list and still browsed the aisles, which falsified the team's hypothesis.
    Task
    Turn the falsified hypothesis into value.
    Action
    A checkout strip surfacing forgotten items from the previous cart and complementary products.
    Read the case study
    Result

      No number on record yet

    • Company-wide AI hackathon

      Situation
      Every vertical had its own problems AI could help with.
      Task
      Source the AI agenda from the businesses instead of guessing it.
      Action
      Created and funded a hackathon where every vertical (rides, groceries, food, car rental, micro-mobility, payments) submitted its top problems against the company's top four goals. My team took the one goal every vertical had declined: raising grocery order value.
      Read the case study
      Result
      • Six verticals set the agenda
      • The declined goal became the AI grocery list: 22% week-one adoption
    • AI Enablement charter

      Situation
      Every Careem vertical needed design, engineering, PRD and data help to put AI to work.
      Task
      Pitch and found an AI Enablement charter, starting as three people.
      Action
      Pitched and founded the charter as three people; it became Careem's central AI and platform function and the implementation partner for every vertical across design, engineering, PRDs and data. The team's tooling moved from ChatGPT to Gemini to Claude Code.
      Read the case study
      Result
      • Up to 80% of commercial and operations workflows run through AI
      • From founder and board level down to ops executives
    • Ask Careem

      Situation
      Process knowledge sat across Confluence, Notion and Drive.
      Task
      Give every employee answers and one-click actions from one place, safely.
      Action
      A retrieval assistant over Confluence, Notion and Drive process docs, in Slack, that raises Jira tickets and runs workflows in one click. Agent actions were validated on a shadow replica of production before rollout; it regenerates its own documentation whenever features ship.
      Read the case study
      Result
      • ~98% accuracy after rollout, with thumbs up and down feedback
    • Merchant onboarding AI

      Situation
      Restaurant onboarding took six days.
      Task
      Cut it with AI.
      Action
      Menu ranking and clustering, image-quality enhancement and dish classification (including veg and non-veg) for restaurant onboarding.
      Read the case study
      Result
      • Merchant onboarding from 6 days to 1
    • AI merchant tooling and dynamic pricing

      Situation
      The merchant platform was being rebuilt around four personas.
      Task
      Help merchants sell more with AI.
      Action
      AI tools for merchants on the platform, including dynamic pricing.
      Read the case study
      Result
      • Merchant revenue +24%
    • Restaurant and merchant platform rebuild

      Situation
      The merchant platform had to serve owners, managers, restaurant staff and kitchen staff.
      Task
      Rebuild it to the standard of the strongest delivery platforms.
      Action
      Rebuilt after benchmarking against Keeta and DoorDash, redesigned for four personas: owner, manager, restaurant staff and kitchen staff.
      Result
      • Carried the AI tooling that lifted merchant revenue 24% and cut onboarding from 6 days to 1
    • Super Portal

      Situation
      Promotions, inventory, cataloguing, onboarding, quality checks and complaints lived in different places.
      Task
      Put them in one internal platform with role-based access.
      Action
      One internal platform for promotions, inventory, cataloguing, merchant onboarding, quality checks and complaint handling, with role-based access. Design rule: the newest employee should reach anything in five clicks.
      Result

        No number on record yet

      • Selection intelligence

        Situation
        Grocery selection and Food availability had to hold up against other platforms.
        Task
        Run selection intelligence end to end.
        Action
        Ran store-level selection for grocery, and merchant and dish availability for Careem Food benchmarked against other platforms, end to end: signals, matching, gap ranking, routing to action and measurement.
        Result

          No number on record yet

        • Dark-store layout optimisation

          Situation
          Fulfilment-centre zones had to follow demand.
          Task
          Lay out each store by its demand pattern.
          Action
          Work-time studies and computer vision to lay out fulfilment-centre zones by demand pattern, with store-level specialisation across a cluster.
          Result
          • Layouts refreshed about every six months
        • Care automation strategy

          Situation
          Refunds, incorrect fares and fees, and repeat questions drove care volume.
          Task
          A six-month care-automation strategy with two PMs.
          Action
          A six-month strategy with two PMs: one on refunds, incorrect fares and fees, with direct monetary impact; one building a full FAQ corpus to power a later retrieval system.
          Result
          • Surfaced the month-end invoice spike that became Careem for Business
        • Internal agents: bug investigator, research agent and the RCS skill

          Situation
          Bug triage and cross-team reports took days of people's time.
          Task
          Hand that work to agents, with people only confirming.
          Action
          An agent that handles most bug triage, with humans only confirming which step in a flow broke; an internal agent with context across PRDs, specs and databases that turned a multi-day, five-person report chase into a sourced one-pager; and an analysis skill (cross-analysis, dependencies, leakage detection) published on Careem's internal skill marketplace and used across the company.
          Read the case study
          Result
          • A multi-day, five-person report chase became a sourced one-pager
          • The RCS skill is used across the company
        • Team, leadership and mentorship

          Situation
          Five verticals: rides, food, grocery, enterprise and internal platforms.
          Task
          Lead the product team, with engineering and design on a dotted line.
          Action
          Seven direct reports, five product managers and two APMs, with engineering and design working to the charter on a dotted line, across five verticals: rides, food, grocery, enterprise and internal platforms. The AI Enablement charter started as three people and Careem for Business was built by a six-person team. The design intern on that first three-person team is now a design manager, and the engineer who volunteered onto the first grocery-list team now runs Careem's web experience.
          Result
          • 7 direct reports: 5 PMs, 2 APMs
          • Nimble teams of 3 and 6 that built new lines

        Zealth 2023 to 2024

        • Consent-based health-records layer

          Situation
          Patients carried paper files between hospitals that would not accept each other's reports.
          Task
          As co-founder and CPO, build a consent-based records layer on India's ABHA rails.
          Action
          As co-founder and CPO, built a layer on India's ABHA rails that normalised imaging, pathology and lab reports into one longitudinal record, shared through time-limited consent. A patient app, plus a history and outreach tool for doctors and labs.
          Read the case study
          Result
          • One of the first five companies admitted to the government sandbox
        • Five partner groups on one record

          Situation
          The record only worked if every party in care joined.
          Task
          Bring five partner groups onto one record.
          Action
          Government (ABHA sandbox), insurers, hospital chains, diagnostic labs and private clinics.
          Read the case study
          Result
          • Pilot across 8 hospitals and 40 clinics
          • The pilot earned revenue
        • Shutdown

          Situation
          The Government of India deprioritised ABHA, the mission Zealth ran on, and hospital incumbents resisted.
          Task
          Decide whether to wait or stop.
          Action
          Shut Zealth down rather than spend limited capital waiting.
          Read the case study
          Result
          • Lesson: a platform on someone else's rails needs a plan for when those rails move

        Hike 2022 to 2023

        • Messaging to gaming pivot

          Situation
          Hike was moving from messaging to gaming.
          Task
          As VP and Chief of Staff to the CEO, run the company internally and lead the pivot.
          Action
          Piloted five game formats (web3, non-web3, cash, non-cash, freemium) against each other before committing to one.
          Read the case study
          Result
          • 230-person team through the pivot in 6 months
          • $100M in recurring revenue, profitable from day one
        • Two-currency game economy

          Situation
          The freemium tier had to pay for itself.
          Task
          Run Rush's two-currency economy.
          Action
          Built the pay-to-play loop for the freemium tier.
          Read the case study
          Result
          • 8% of new users converted to paid every month
        • Rush VIP tiers

          Situation
          Paying players needed a reason to stay and spend more.
          Task
          Design loyalty for the game.
          Action
          A tiered, gamified loyalty programme.
          Read the case study
          Result
          • User spend +30%
          • D30 retention 12% to 30%
        • Data and Revenue team

          Situation
          Hike had no Data and Revenue team.
          Task
          Set one up.
          Action
          Made A/B testing and pricing governance the default path to ship.
          Read the case study
          Result
          • Margins +20%

        Amazon 2020 to 2022

        • Seller onboarding and gamification

          Situation
          Micro-sellers behind 80% of India volume relied on cyber cafes because Seller Central was web-first.
          Task
          As single-threaded owner of seller success, double onboarding success, measured on a seller's first 100 orders.
          Action
          Redesigned onboarding mobile-first and owned the seller gamification product.
          Read the case study
          Result
          • $130M incremental revenue
        • Top Brands trust signal

          Situation
          Buyers could not tell real D2C brands from fakes.
          Task
          Give good brands a trust signal buyers can see.
          Action
          A product-page trust signal for good D2C brands, built after work on counterfeit and bad-seller detection.
          Read the case study
          Result
          • D2C brand revenue +200%
          • 3% higher conversion
        • Seller quality engine

          Situation
          Fraudulent sellers and items were reaching customers.
          Task
          Block them before they did.
          Action
          An ML engine on 30+ signals that blocked fraudulent sellers and items before they reached customers.
          Read the case study
          Result
          • Returns -25%
        • India Ultrafast Fresh

          Situation
          India Ultrafast Fresh was starting from scratch.
          Task
          Join the founding team.
          Action
          Unified inventory across warehouses.
          Read the case study
          Result
          • Daily orders +20%
          • Fulfilment cost -10%

        Zomato 2018 to 2020

        • Cyclist fleet

          Situation
          80 to 85% of orders came from within about 3 km, but delivery required a motorcycle.
          Task
          Drive “shutdown” to zero at a cost per order that pays.
          Action
          Order data showed 80 to 85% of orders came from within about 3 km, so short trips went to cyclists, unlocking supply from milk and newspaper delivery riders who sat idle at lunch and dinner. Piloted in Delhi, Gurgaon, Noida and Hyderabad, then rolled out nationally.
          Read the case study
          Result
          • 90K cyclists from zero
          • 43% of orders at 50% lower cost
          • Cost per order ~₹120 to ~₹78
        • Rider safety and insurance

          Situation
          No underwriter would cover cyclists.
          Task
          Make the new supply safe and insured.
          Action
          No underwriter would cover cyclists, so I introduced delivery-partner insurance at Zomato for the first time. Built guardrails into assignment: no night orders for women riders, no multi-floor buildings for riders with disabilities.
          Read the case study
          Result
          • Zomato's first delivery-partner insurance
        • The hidden cyclist-or-biker choice

          Situation
          Showing customers a cyclist-or-biker choice raised complaints, though measured ETAs differed by only 30 to 45 seconds.
          Task
          Cut complaints without slowing delivery.
          Action
          Kept the choice hidden; a fast-follow made assignment concentric: cyclists first close in, bikers otherwise.
          Read the case study
          Result

            No number on record yet

          • The "shutdown" north star

            Situation
            Paying more bought only marginal supply.
            Task
            Define what success meant for fulfilment.
            Action
            Defined the north star as "shutdown", the share of time the app showed nothing deliverable in an area, with a goal of zero rather than a reduction.
            Read the case study
            Result
            • The goal the whole 14-product fulfilment portfolio worked to
          • Payouts and rate cards

            Situation
            One payout structure per city could not pay a two-hour cyclist and a twelve-hour biker fairly.
            Task
            Rebuild payouts with the finance org.
            Action
            Rebuilt rider payouts in six phases with the finance org: multimodal payouts, then incentive tiers by partner type, then cohort-level rate cards and part-time rate cards.
            Read the case study
            Result
            • Rate cards for cohorts as small as 10 riders
            • Riders engaged more, earned more and stayed longer
          • Promotion and fee platform

            Situation
            Customers had to do the maths across bank, wallet, partner and Gold offers.
            Task
            Build Zomato's first promotion platform.
            Action
            Zomato's first promotion platform: bank, wallet, partner and Gold offers stacked automatically in one cart, plus a platform-fee structure that could be added, removed and targeted by cohort.
            Read the case study
            Result

              No number on record yet

            • Karma Score and dynamic pricing

              Situation
              Abuse and flat pricing ate into margin.
              Task
              Protect unit economics with ML.
              Action
              An ML fraud and abuse system, alongside a dynamic pricing engine.
              Read the case study
              Result
              • Platform abuse -90%
              • Margins +18%
            • Fulfilment pod and P&L

              Situation
              Zomato was growing from 5 to 500 cities.
              Task
              Lead the fulfilment product pod and own the 250-city P&L on a $20M budget.
              Action
              APMs and program managers across assignment, serviceability, payouts, and fraud and cash collection.
              Read the case study
              Result
              • 250-city P&L from -20% to +16% EBITDA

            Travel Triangle 2017 to 2018

            • Weekend getaways

              Situation
              Repeat had been about 5% over nearly five years.
              Task
              Give travellers a reason to come back every year.
              Action
              Domestic weekend getaways near Mumbai, Pune, Bengaluru and Delhi.
              Read the case study
              Result
              • 90% of repeat travellers within six months
              • 40% of revenue within six months
              • 8,000+ people sent on offbeat trips such as Rishikesh
            • Referral and loyalty loop

              Situation
              When one person in a group marries, many more follow over the next few years.
              Task
              Turn one traveller into many.
              Action
              Referral rewards and loyalty rewards across a three-sided marketplace of travellers, local travel agents and on-ground providers, with trips per converted traveller as the north star.
              Read the case study
              Result
              • One conversion led to about 20 trip conversions
            • Lead scoring and conversion engine

              Situation
              Acquisition cost was very high.
              Task
              Convert more of the leads already paid for.
              Action
              A retargeting and conversion engine that scored and re-engaged leads on user profile, location and 25+ profile attributes, with a 40-person CX team.
              Read the case study
              Result
              • Lead-to-conversion +23%

            Delhivery 2015 to 2017

            • DMiles prepaid wallet

              Situation
              Revenue leakage ran at about 20% of monthly revenues: small e-commerce sites closed within three or four months, exactly the credit line logistics extended.
              Task
              Stop the leakage.
              Action
              Moved risky long-tail B2B shippers from credit to a prepaid wallet.
              Read the case study
              Result
              • $3M unrealised revenue recovered
              • Leakage -95%
            • AddFix address resolution

              Situation
              Indian addresses are free text, so one door arrives written many ways.
              Task
              Give routing and capacity planning a structured location.
              Action
              Clustered variants into uniform locations by learning from successful deliveries, delivery alternates and shared markers.
              Read the case study
              Result
              • Later offered to Amazon as a service
            • Pin-code reach

              Situation
              Delhivery's network had to reach more of India's pin codes.
              Task
              Turn insights into plans the teams could execute.
              Action
              Translated insights into actionable plans with the teams responsible for coverage.
              Result
              • Pin-code reach +40%, to 7,200, in 3 months
            • LTL product launch

              Situation
              The network had capacity it was not using.
              Task
              Launch a less-than-truckload product.
              Action
              Worked with C-level executives to launch the LTL product.
              Result
              • Network capacity utilisation +15%
            • Drop@Store

              Situation
              Shippers needed more places to hand over parcels.
              Task
              Define the value proposition for a Drop@Store model.
              Action
              Defined the Drop@Store value proposition and launched it in several cities.
              Result

                No number on record yet

              • Sales operations: Salesforce and weekly reviews

                Situation
                Sales lacked detailed opportunity sizing and visibility.
                Task
                Give the businesses one view of the pipeline and a rhythm to act on it.
                Action
                Evaluated and drove the Salesforce implementation, and instituted weekly reviews across six businesses.
                Result
                • Weekly reviews across 6 businesses

              Early career 2012 to 2013

              • Bharti Airtel: sales trainee, sales and distribution

                Situation
                Airtel 3G and Airtel Money needed reach in villages around Jamshedpur.
                Task
                Activate both brands and understand what made retailers perform.
                Action
                Ran road and panchayat shows in villages, studied consumer engagement for brand building, and analysed retailer performance from primary data I collected from 500 retailers.
                Result
                • Primary data from 500 retailers
              • Pulsar Products, Cleveland, USA: corporate strategy (MBA live project)

                Situation
                Pulsar Products wanted to grow its brand in the American market and expand through partners.
                Task
                Work with the CEO on brand expansion and a go-to-market plan for its subscription kit product.
                Action
                Briefed agencies, evaluated their pitches and finalised the digital marketing plan; negotiated with 10 potential partners for inorganic growth, identified clients in India and China, and designed the go-to-market for those markets.
                Result
                • 10 potential partners negotiated with
              • Tata Tinplate, India: business strategy (MBA live project)

                Situation
                Tata Tinplate was heading into its centenary year, 2020.
                Task
                Work in the corporate strategy team with the CEO and an international team of students.
                Action
                Built an online and offline brand strategy for a ₹20 crore budget, a growth plan for pricing and distribution in international markets, and a turnaround strategy around the right product mix.
                Result
                • Projected 40% revenue growth over 5 years (a plan, not a measured result)
              • Mary Kay, Hangzhou, China: marketing simulation (MBA project)

                Situation
                Mary Kay needed to adapt to China's tier II cities and interior markets.
                Task
                Find how the business should change to reach them.
                Action
                Analysed the business model in China, ran exploratory primary research on content, pricing and consumer preferences, and built a value network and proposition for interior markets.
                Result

                  No number on record yet

                Education 2013 to 2015

                • MBA, XLRI Jamshedpur

                  Exchange programmes at Tongji University, China, and Case Western Reserve University, USA. Live projects with Pulsar Products (USA), Mary Kay (China) and Tata Tinplate (India).

                  Result
                  • Top 5% of batch
                • BBA, Central University of Jharkhand

                  Strategy and Marketing. President of India Scholarship. Founded Unnayan, which gave village students free tuition from student volunteers.

                  Result
                  • Top 1% of class
                  • 7,000+ students reached through Unnayan

                A number appears only where it is consistent across my own CVs and interviews. Where my own tellings differ, the item is listed without the figure.

                Career, 2015 to nowThe journey across seven companies, the full timeline and education.
                Career

                Seven sides of the market. One job.

                ShippersTravellersRidersSellersPlayersPatientsPartners

                Every move put me on a different side. The job never changed: make that side want to stay, and prove it with a number.

                1. Dec 2015 to Jun 2017DelhiveryManager, Business OperationsOwned: Shippers
                  The move
                  Moved risky long-tail B2B shippers from credit to a DMiles prepaid wallet, and built AddFix to make free-text addresses routable.
                  The number
                  $3M recovered, leakage -95%. One of the first 30 employees.
                  Read the case
                2. Jun 2017 to Jul 2018Travel TriangleProduct Leader, Customer ExperienceOwned: Travellers
                  The move
                  Turned a once-in-a-lifetime holiday into weekend getaways, referral rewards and a repeat habit.
                  The number
                  90% of repeat travellers and 40% of revenue within six months; lead-to-conversion +23%.
                  Read the case
                3. Sep 2018 to Dec 2020ZomatoGroup Product Manager, Online OrderingOwned: Delivery riders
                  The move
                  Unlocked cyclists for short trips, rebuilt payouts down to cohort rate cards, and added insurance and safety guardrails.
                  The number
                  90K cyclists from zero; a 250-city P&L from -20% to +16% EBITDA.
                  Read the case
                4. Dec 2020 to Apr 2022AmazonProduct Leader, Seller Growth & Quick CommerceOwned: Sellers
                  The move
                  Rebuilt onboarding mobile-first for micro-sellers and gave good brands a trust signal buyers could see.
                  The number
                  $130M incremental revenue; D2C brand revenue +200%.
                  Read the case
                5. Apr 2022 to Mar 2023HikeVP, Chief of Staff to CEOOwned: Players
                  The move
                  Two currencies, a pay-to-play loop and VIP tiers, through a pivot from messaging to gaming.
                  The number
                  $100M recurring revenue, profitable from day one; 8% of new users paying each month.
                  Read the case
                6. Apr 2023 to Jan 2024ZealthCo-founder & CPOOwned: Patients and providers
                  The move
                  One consent-based health record that government, insurers, hospitals, labs and clinics would all use.
                  The number
                  One of the first five companies in India's ABHA sandbox; 8 hospitals and 40 clinics piloted.
                  Read the case
                7. Mar 2024 to nowCareemLead PM, New Bets (AI & Enterprise)Owned: Partners and companies
                  The move
                  Opened the platform to partner businesses and made companies a paying side, then took AI across the company.
                  The number
                  A car-rental partner's GTV via Careem from ~5% to ~96%; up to 80% of ops workflows on AI.
                  Read the case
                Full timeline with education
                1. Mar 2024 to now
                  Careem · Lead Product Manager, New Bets (AI & Enterprise)

                  Tenants, Careem for Business, Careem Plus and the AI Enablement charter. Seven direct reports: five PMs and two APMs.

                2. Apr 2023 to Jan 2024
                  Zealth.club · Co-founder & CPO

                  Health-records network on India's ABHA rails: one of the first five companies in the government sandbox, with government, insurer, hospital, lab and clinic partners.

                3. Apr 2022 to Mar 2023
                  Hike · VP, Chief of Staff to CEO

                  Messaging to gaming pivot and the Rush economy.

                4. Dec 2020 to Apr 2022
                  Amazon · Product Leader, Seller Growth & Quick Commerce

                  Seller onboarding, Top Brands, the seller quality engine, founding team of India Ultrafast Fresh.

                5. Sep 2018 to Dec 2020
                  Zomato · Group Product Manager, Online Ordering

                  Fulfilment, rider payouts, promotions and fraud through growth from 5 to 500 cities.

                6. Jun 2017 to Jul 2018
                  Travel Triangle · Product Leader, Customer Experience

                  Repeat and referral loop, weekend getaways, lead scoring.

                7. Dec 2015 to Jun 2017
                  Delhivery · Manager, Business Operations

                  Among the first 30 employees. DMiles and AddFix.

                8. 2013 to 2015
                  XLRI Jamshedpur · MBA

                  Top 5% of batch. Exchange at Tongji University, China, and Case Western Reserve University, USA. Live projects with Pulsar Products in Cleveland, USA (a subscription kit product), Mary Kay in Hangzhou, China and Tata Tinplate in India.

                9. 2012 to 2013
                  Bharti Airtel · Sales Trainee, Sales and Distribution

                  Airtel 3G and Airtel Money activation in villages around Jamshedpur; retailer analysis from 500 retailers.

                10. 2009 to 2012
                  Central University of Jharkhand · BBA, Strategy & Marketing

                  Top 1% of class, President of India Scholarship. Founded Unnayan, which gave 7,000+ village students free tuition from student volunteers.

                The mapWho I built for and where: a Venn of the sides of the market and a ten-industry grid.
                The map

                Every side of the market. Ten industries.

                Two ways to see the same career: who I built for, and where. Pick any part to see the work behind it.

                Who I built for

                ConsumersPartners & supplyBusinessesHike ·Careem PlusZomato ridersDelhivery shippersZomato ·Amazon ·Zealth ·Travel TriangleCareem forBusinessSwapp ·merchantsCareem
                All three at once

                Customers, partner businesses and companies, on one set of payment rails.

                Where, and what I built

                IndustryMarketplace & platformGrowth & loyaltyMoney & paymentsAI & dataOperations
                Super-appCareem
                Food deliveryZomato · Careem Food
                Grocery & quick commerceCareem · Amazon
                E-commerceAmazon
                TravelTravel Triangle
                GamingHike
                HealthZealth
                LogisticsDelhivery
                Mobility & home servicesCareem
                Enterprise & B2BCareem · Delhivery

                31 intersections with shipped work. Tap a dot to open it in the full record.

                AI runs through all of it: the grocery list, AI Meals, Ask Careem, merchant onboarding and the agents behind Careem's operations.

                How I take on a broad problemThe method, and the 19 Careem and 14 Zomato products it produced.
                What I'm hired for

                A broad, unstructured problem. A portfolio that ships.

                I'm rarely handed a spec. I'm handed a problem area and a goal. I find what can be built, ship it with metrics, remove pain points along the way, and re-architect when the old design won't scale.

                A loop: map, wedge, ship and measure, re-architect, then map again from what was measured 1Map2Wedge3Ship and measure4Re-architect Each turn starts from what the last one measured.
                1. MapFind where the goal is really stuck: data, users, operations.
                2. WedgePick the smallest thing that can be built and measured.
                3. Ship and measureOne metric per product, killing pain points on the way.
                4. Re-architectRebuild the foundation when scale demands it.
                Overarching goal

                Grow Careem beyond the verticals it runs itself, and run all of it leaner with AI.

                The brief was a direction, not a spec. Four pillars came out of it, and every product below ladders up to one of them.
                How the pieces compound

                Partners plug inMore to buy in one appAdopters triple their spendPartners grow with Careem (~5% to ~96% of GTV)More partners want in↺

                New supply, without new verticals

                New paying customers

                Grocery and food: orders that pay

                A leaner company, through AI

                Overarching goal

                Drive “shutdown”, the time the app shows nothing deliverable, to zero, at a cost per order that pays.

                One north star, four pillars. No single product could move it; the portfolio did.
                How the pieces compound

                Short trips go to cyclistsMore riders at peakLess shutdown, more ordersCost per order ~₹120 to ~₹78Room to pay each cohort fairlyRiders stay↺

                More supply

                Riders who stay

                Demand that pays

                Trust and unit economics

                Pick any product to see what it did and how it moved the goal.

                Five habits I don't negotiate onEach one with the project that taught it.
                How I work

                Five habits I don't negotiate on

                Each one came from a project that would have gone worse without it.

                1. 01

                  An MLP, never an MVP.

                  Minimum lovable, not minimum viable. A narrow scope, finished properly, beats a wide one nobody comes back to.

                  The grocery list did one thing well: 65% of adopters were back within two weeks.
                2. 02

                  Take the problem everyone has written off.

                  The interesting work is usually the goal other teams have already decided can't move.

                  At Careem's AI hackathon every vertical passed on grocery basket size. We took it.
                3. 03

                  Win the argument by building.

                  A working thing ends a debate faster than a better slide.

                  A prototype I built on Lovable settled the grocery list design; a fake-door page proved Careem for Business in two weeks.
                4. 04

                  Refuse the easy lever.

                  Discounts move a number this month and train customers forever.

                  Instead of a big-basket discount, country-of-origin tags made quality visible.
                5. 05

                  Build, operate, then hand it over.

                  I build it, run it until it works, and leave it with the team that owns it.

                  Ask Careem reached ~98% accuracy and regenerates its own documentation as features ship.
                Selling with partners and to enterprisesThe commercial side of the work at Careem, Amazon and Delhivery.
                Go to market

                Selling with partners and to enterprises

                Every partner product I've owned had a commercial motion attached, and I carried it until a sales team could.

                Careem

                Signed Tenants partners on agreed commercial terms across three countries, turned around a strained partnership with Swapp into an exclusivity deal with equity for Careem, and built lasting partnerships with Justlife and Washmen, and sold Careem for Business to its first companies myself.

                Amazon

                Owned seller success for the micro-sellers behind 80% of India volume, and built Top Brands so D2C brands could sell on trust signals.

                Delhivery

                Moved B2B shipper accounts onto the DMiles prepaid model, and AddFix, our address engine, was later offered to Amazon as a service.

                Things I've built myself, and outside workFake doors, this site, Claude skills, Cubby, Journey Log, and Unnayan.
                Builder

                Things I've built myself

                With Claude Code, Lovable and Replit, the distance between an idea and a working product is mine to close. Each one in the same four steps.

                At work

                Fake doors and prototypes

                Situation
                Careem for Business had been shelved before, and the grocery list's form factor was stuck in internal debate.
                Task
                Settle both with something working, not a slide.
                Action
                Built the Careem for Business fake-door page on Lovable myself, and the single-page grocery list prototype that won the form-factor debate.
                Result
                • 200+ interest forms from ~70 companies in two weeks
                • The list shipped and hit 22% week-one adoption against a 5 to 7% target
                This website

                sauravpatro.com

                Situation
                A recruiter should understand my work in seconds, and be able to check every claim.
                Task
                Build and run it myself.
                Action
                A static site on Cloudflare Pages, built with Claude Code and deployed from GitHub on every push: role views, 12 cases, a searchable record of every delivered item, and files for AI readers.
                Result
                • Home page cut from about 20 screens to about 5.5, with email on the first screen
                • 50 delivered items documented, each with its number where my sources agree
                Claude skills

                Product Board and teardown skills

                Situation
                Venture reviews and competitor teardowns took hours of manual work.
                Task
                Package them as reusable Claude skills.
                Action
                A multi-pod venture review skill, and a competitive app-teardown skill that pulls from App Store feeds, Google Play and Product Hunt, in chat or as a server-side pipeline.
                Result
                • Used on this site: the Product Board reviewed the v36 redesign

                No usage numbers yet.

                Consumer app

                Cubby

                Situation
                In a shared household, everyone added to a baby-care app sees everything.
                Task
                Build one where private things stay private.
                Action
                Built on Firebase, with per-baby access controls, an audit step when family members are added, and a home feed of daily notes with per-recipient privacy.
                Result

                Built for my own family. No usage numbers yet.

                Consumer app

                Journey Log

                Situation
                I wanted one place for training, body composition and goals.
                Task
                Build it, and finish it properly.
                Action
                A single-file web app with a 45-exercise library, body-composition logging and a goals system, deployed on Cloudflare Pages.
                Result

                Built for my own use. No usage numbers yet.

                Outside work

                Where the habits started

                Unnayan

                At university I founded Unnayan, which gave 7,000+ village students free tuition from student volunteers. It was my first marketplace: volunteers on one side, students on the other.

                On stage

                At university I co-hosted a quiz with Barry O'Brien for an audience of 100,000, was the only student on the committee for the 150 years of Tagore celebrations, and won state-level debating and business-plan competitions.

                Curious about

                Brand design, and orchestrating several AI models and agents to work together. This site was built with Claude.

                Run a delivery marketplace for a minuteA toy with the trade-offs I worked through at Zomato.
                Play

                Run a delivery marketplace for a minute

                Four levers, four goals. It's a toy, but the trade-offs are the ones I worked through at Zomato.

                You run food delivery in one city. Hit all four goals at once: 5,500+ orders a day, delivery in 30 minutes or less, riders earning ₹900+ a day so they stay, and no loss on each order.

                Orders a day0goal 5,500+
                Delivery time0goal 30 min or less
                Rider earnings a day0goal ₹900+
                Profit per order0goal ₹0 or more

                A toy model. Its numbers are illustrative, not Zomato data. The results in the green box are real.