Indic AI Product and Developer Platform

Product challenge

A capable model is not yet a product. Sarvam needed a complete path from agentic Indic AI to something enterprises, developers, operators, and paying customers could understand, integrate, configure, observe, and purchase.

Product and engineering approach

Turn model capability into product experience

• Built a React and TypeScript SDK for streaming audio with synchronized interface states, plus a Flutter SDK for chat and in-app transitions.
• Delivered a Next.js experience that made real-time audio and interface responses feel like one coherent interaction.

Make the system usable by builders and operators

• Designed an authoring dashboard for agentic applications with knowledge, memory, and state transitions.
• Built debugging tools for audio and chat flows so product and engineering teams could inspect behavior rather than treat the model as a black box.
• Added analytics that translated user interactions into actionable product signals.

Connect the product to the business

• Integrated billing with Sarvam Model APIs and the Azure marketplace.
• Implemented subscriptions, usage metering, and checkout workflows.
• Added Grafana, Sentry, automated quality checks, and CI/CD so the team could operate and evolve the platform with confidence.

Outcome

• Closed the gap between an AI model and an adoptable product for end users, developers, administrators, and enterprise buyers.
• Reduced developer friction with SDKs, authoring, and debugging experiences.
• Enabled commercial use through metering, subscriptions, checkout, and marketplace integration.
• Improved product learning and reliability through analytics, monitoring, and dependable delivery pipelines.

This work shaped how I approach AI products: start with the user’s job, then engineer the model interaction, deterministic workflows, business model, and operational feedback loop together.