# Rajas Bhagat | AI Product Builder

> Rajas Bhagat is an AI product builder based in Barcelona, Spain. He combines applied AI, product judgment, and customer insight to build useful products that real teams can deploy, trust, and use. He is an MBA candidate at IESE Business School with experience across Sprinklr, WebEngage, and Deloitte.

## Core areas

- AI Builds: RAG systems, agentic workflows, context engineering, evaluation, and deployment.
- Enterprise Product: customer discovery, AI features, onboarding, enablement, adoption, and automation.
- Growth and Strategy: activation, retention, monetization, lifecycle strategy, and go-to-market systems.
- Product Process: translating field signals into product decisions, prototypes, and measurable outcomes.

## Tools and methods

- AI and LLM: OpenAI, Claude, Gemini, LangChain, LlamaIndex, ChromaDB, Vertex AI.
- Product and analytics: user research, product strategy, Amplitude, Mixpanel, PostHog, Looker.
- Build and delivery: Python, TypeScript, React, n8n, Supabase, workflow automation, evaluation harnesses.

## Proof

- 200+ enterprise clients reached through GenAI, adoption, and customer success work at Sprinklr.
- 70+ user interviews conducted to ground product and adoption decisions.
- 18% retention lift and 5% activation lift through product-led growth work at WebEngage.
- 12% average order value lift through product-led growth work.
- 60% support ticket reduction and 70% faster resolution for basic queries through RAG-based support systems.

## Main pages

- [Home](https://rajasb.com/): An interactive introduction to Rajas and his work across AI, enterprise product, growth, and product process.
- [Selected Work](https://rajasb.com/work): AI Builds, Enterprise Product, Growth and Strategy, and Programs.
- [Profile](https://rajasb.com/about): Work experience, product approach, tools, proof, and contact details.

## AI build case studies

- [Learning RAG](https://rajasb.com/work/learning-rag): A hands-on platform covering more than 20 advanced retrieval techniques.
- [Socratoys](https://rajasb.com/work/socratoys): A voice-first AI learning companion with multi-agent architecture and long-term memory.
- [Mettis AI](https://rajasb.com/work/mettis-ai): Driving-behavior analytics using causal inference and learned world models.
- [Automated Competitor Intelligence](https://rajasb.com/work/competitive-intelligence): A clinical-trial intelligence system that translates events into strategic implications.
- [Creative Brief Automation](https://rajasb.com/work/creative-brief-automation): A human-in-the-loop system that turns references and brand constraints into production-ready briefs.

## Enterprise product and growth case studies

- [Sprinklr Onboarding](https://rajasb.com/work/sprinklr-onboarding): Enterprise onboarding and adoption redesign.
- [RazorpayX](https://rajasb.com/work/razorpayx): Engagement and retention strategy for business banking.
- [Chargebee](https://rajasb.com/work/chargebee): Account-based marketing strategy for subscription infrastructure.
- [Calendly](https://rajasb.com/work/calendly): Monetization and upgrade-trigger analysis.
- [Keka](https://rajasb.com/work/keka): Full-funnel growth strategy for HR SaaS.
- [Retool](https://rajasb.com/work/retool): Growth model for developer tools.
- [Fund II Workspace](https://rajasb.com/work/fund2-workspace): A shared multi-agent workspace for MVP builders.

## Experience and education

- Sprinklr: GenAI product work, RAG support systems, enterprise onboarding, and adoption across 200+ clients.
- WebEngage: product-led growth, lifecycle strategy, activation, and retention.
- Deloitte: QA automation, partner integrations, and system reliability.
- IESE Business School: MBA candidate, class of 2027.
- MIT Pune: B.Tech.

## Contact

- Email: rajassbhagat@gmail.com
- LinkedIn: https://www.linkedin.com/in/rajassbhagat/
- GitHub: https://github.com/Rajasbhagat
- Location: Barcelona, Spain