Razorpay AI Buildathon — Build. Show. Get hired.
Think you can build real AI? Prove it. A student-only program to discover and hire our next generation of AI Builder Interns. Students only. 6 or 12 month AI Builder Internship. In-person, Bangalore, from September.
No resume screening. No long application. Four steps: pick a track, build something real, show your work (a public repo, a 5 minute pitch video, the architecture), and if it has signal we call you in.
Tracks
01 — AI Growth & Agentic Commerce
Grow the merchant’s revenue, and make them sellable to AI buyers.
Build an agent that grows revenue for a merchant on Razorpay test-mode APIs, or that makes a merchant transactable by an AI buyer end to end.
Why now: NPCI’s UAP and the global protocol race (ACP, AP2, x402) make agent-to-agent commerce the open problem of the year, and Razorpay’s in-app pilots are already live.
Example directions:
Conversational in-app checkout
Agent-readable catalog
Upsell & cross-sell agent
Campaign orchestrator.
The bar: Every money action explainable, bounded and gated. Show the audit trail and one failure handled gracefully.
02 — AI Risk Manager
Stop the merchant losing money to fraud, returns and chargebacks.
Build a working detector, verifier or auto-responder for one class of loss, with measured precision and recall on a held-out test set.
Why now: AI-enabled fraud is hitting Indian BFSI while returns and chargebacks quietly eat margin. This track surfaces the risk and ML minded builders the others miss.
Example directions:
Chargeback evidence responder
Return-risk scorer
Fraud-spike detector
Abuse-ring sentinel.
The bar: Honest metrics including false-positive cost. Strictly defense-only: anything offense-capable is disqualified.
03 — AI Revenue Recovery
Find revenue that’s slipping away and win it back.
Build an agent that detects revenue at risk, determines the right intervention, and executes a bounded recovery workflow: from payment failures and checkout abandonment to overdue receivables.
Why now: Revenue loss rarely happens in one clean step. A payment degrades, a checkout gets abandoned, a subscription fails, or an invoice goes overdue. AI can now close the loop from detecting the problem to diagnosing it, choosing the right intervention, and recovering the money.
Example directions:
Payment degradation → root cause → recovery action
Checkout drop-off recovery
Failed-subscription recovery
B2B receivables chaser
Mandate retry sequencer
Hinglish voice recovery
Promise-to-pay tracker.
The bar: Don’t just identify the problem. Show measured money recovered across a batch, with compliant escalation, stopping rules, and an audit trail.
04 — AI Finance Controller
Run the books and the cash position.
Build an agent that closes one finance-ops loop across a 50+ record batch of synthetic data, reporting its match rate and the exceptions it could not resolve.
Why now: The 2026 builder consensus: verification capacity, not generation speed, is the bottleneck. Reconciliation, settlement and forecasting are still done by hand.
Example directions:
Multi-source reconciliation
Settlement Q&A agent
Forward cash forecaster
Tax-line matcher.
The bar: Throughput plus measured accuracy plus an honest exception list. One cherry-picked match proves nothing.
05 — Open Track
Build what you believe should exist.
Have an idea that doesn’t fit the tracks above? Build it. Pick a real problem, use AI meaningfully, and show us something that works. Any domain, workflow, or user is fair game.
Why now: The best ideas don’t always fit a predefined category. This track exists for builders who see an opportunity we didn’t.
Example directions:
Surprise us
Solve a problem you deeply understand
Build something we haven’t thought of.
The bar: Open doesn’t mean easier. Show a real problem, a working product, meaningful use of AI, and evidence that it creates value. The same bar for execution, reliability, and depth applies here.
The offer
₹75,000 (monthly stipend) · 6 or 12 (months, your choice) · In-person (Bangalore, from September). Shortlisted builders go straight to a panel. No aptitude test. No group discussion.
Your code speaks louder than your resume.