Madhur Jain

Product capabilities, with evidence.

My strongest range is growth and monetization, evaluated AI workflows, product strategy, and data-informed delivery. Each area is tied to professional outcomes or clearly labelled personal build proof.

Evidence across contexts.

85%
NL-to-SQL accuracy
Golden-dataset evaluation at PRISM
6 teams
Running their own analysis
Adoption of the analytics agent at PRISM
+15%
Trial-to-paid
Web-to-app subscription migration at SplashLearn
INR 175 Cr
Aqualogica run rate
Roughly $21M a year on a site I owned at Honasa

AI products and workflow automation

Turn business questions and repetitive operating work into evaluated AI workflows.

Evidence

At PRISM I shipped a two-agent natural-language-to-SQL workflow that reaches 85% accuracy on a golden dataset of business queries, now used by six teams. I am building a general-manager operations agent across five functions, in pilot at 40 UK and Europe properties, against efficiency and accuracy criteria I defined.

Read the evaluated AI workflow case
  • Agentic workflows
  • LLM evaluation and benchmarking
  • Golden-dataset evaluation
  • Text-to-SQL
  • RAG
  • Prompt design
  • Release validation

Growth, monetization, and conversion

Find leverage in customer journeys and turn it into conversion, subscribers, and revenue.

Evidence

Pricing transparency and a dynamic fee module at PRISM, Android subscriber growth and web-to-app migration at SplashLearn, and homepage, search, and referral funnels at Honasa. The levers differ; the method of finding them does not.

Read the mobile growth case
  • Pricing and fees
  • Subscription growth
  • Funnel analytics
  • Experimentation
  • Referral and acquisition systems
  • Retention and activation
  • D2C ecommerce

Product strategy and delivery

Move ambiguous opportunities from a decision to a launch with teams aligned around the customer and business.

Evidence

Across US consumer pricing and conversion, Android subscriber growth, and multi-brand ecommerce systems, I have set roadmap, tradeoffs, launch conditions, and stakeholder alignment, and owned deployment and release validation for the AI systems I ship.

Review product ownership by role
  • Roadmapping
  • GTM and launch
  • PRDs and specs
  • Release ownership
  • Regulatory delivery
  • Stakeholder alignment

Data fluency and technical collaboration

Work fluently with the systems, instrumentation, and analysis that make product decisions defensible.

Evidence

A computer science degree, SQL and Python in daily use, and API and event architecture designed with engineering to support one million transactions a day at Honasa. In Coach I write the product myself across three platforms.

See technical delivery in Coach
  • SQL
  • Python
  • Product analytics
  • Data pipelines
  • APIs and event architecture
  • Instrumentation

Tools I work in.

AI and data
LangChain, LangGraph, RAG, Vector databases, SQL, Python, Golden-dataset evaluation
Analytics and BI
GA4, Mixpanel, CleverTap, MoEngage, Looker, Power BI, Metabase
Build and design
Figma, JIRA, Cursor, Claude, Codex, Lovable, Xcode, Android Studio