Your AI product
growth team.
Einstein Labs turns customer evidence into prioritized specs, production-ready software, launch assets, analytics, and monetization experiments — all in 30 days.
Apply for a 30-day sprint →Built for founders and product teams that need to decide, build, launch, measure, and monetize faster.
AI teams do not lose because they lack ideas.
They lose because the loop is broken.
Customer feedback lives in calls, Slack, support tickets, analytics tools, founder notes, and half-written roadmaps. Engineering works from incomplete specs. Launches happen without a measurement plan. Usage data arrives too late. Monetization gets bolted on after costs are already leaking.
Roadmaps are not evidence-based
Teams collect user feedback but struggle to turn it into confident product decisions.
Specs do not survive engineering
Product intent gets lost between research, requirements, implementation, and QA.
Shipping does not equal learning
Features launch without the instrumentation needed to know whether they worked.
AI monetization is different
Credits, usage, model costs, limits, overages, and margins need infrastructure from day one.
Einstein Labs compresses that entire loop.
One operating system for product growth.
Einstein Labs connects the work normally split across product strategy, engineering, analytics, marketing, video, and billing. Each part feeds the next, so every sprint compounds into better product judgment and faster execution.
Ingest interviews, support tickets, product usage, business goals, and repo context.
Identify highest-leverage opportunities ranked by impact, confidence, effort, and urgency.
Generate human-readable and agent-ready specs with user flows, data models, and acceptance criteria.
Use Polaris to turn specs into production-ready full-stack software, prototypes, or product changes.
Create written content, product narratives, and video assets that explain what changed and why.
Instrument usage, track adoption, capture signals, and turn behavior into the next product decision.
Design credits, entitlements, usage pricing, limits, and billing flows for AI-native products.
Two ways to move faster.
Start with the product if you know what you want to build. Start with the sprint if you need the whole loop.
Polaris
Spec-driven AI app builder.
Turn product specs, PRDs, user flows, and data models into full-stack apps and product changes. Built for founders and teams who need production-grade software, not throwaway prototypes.
Product Growth Sprint
30 days from evidence to shipped product.
Give us your customer calls, support tickets, analytics, roadmap, and repo context. We produce the strategy, specs, product changes, launch assets, measurement plan, and monetization recommendations.
Build production apps from specs, not prompts.
Most AI app builders start with a vague prompt. Polaris starts with product intent. It reads structured specs, user flows, data models, acceptance criteria, and technical constraints so the generated application is easier to inspect, edit, and ship.
- Import a PRD, spec, or structured product brief.
- Generate full-stack app foundations.
- Preserve product intent across frontend, backend, data, and flows.
- Iterate through agent-ready change requests.
- Share demos and previews with your team.
Your next product bet, shipped and measured in 30 days.
The Product Growth Sprint is for founders who need more than a tool. Einstein Labs analyzes your evidence, finds the highest-leverage opportunities, writes the specs, builds or prototypes the product changes, creates launch assets, instruments measurement, and recommends the next monetization move.
We ingest interviews, support tickets, analytics, roadmap notes, business goals, and repo context. Praxiom identifies themes, gaps, customer pains, and prioritization logic.
We turn the highest-priority opportunities into human-readable and agent-ready specs with user flows, data models, edge cases, and acceptance criteria.
Polaris builds or prototypes the chosen product changes. Prism and Parallax support launch content and product video where relevant.
Pulse instruments usage and adoption signals. Pylon supports pricing, credits, usage, and entitlement recommendations for AI-native products.
Six agents. One product growth loop.
Einstein Labs is powered by a set of integrated products built around the full lifecycle of an AI-native software company.
Turns interviews, product data, and customer evidence into insights, feature recommendations, prioritization, and agent-ready specs.
Turns structured product intent into full-stack applications and production-ready product changes.
Measures how users interact with what you shipped and turns usage into the next product decision.
Researches, drafts, edits, and publishes product-led content built from your strategy and customer insights.
Uses product, audience, asset, scene, and performance graphs to generate product marketing videos and variants.
Helps AI companies design credits, usage metering, entitlements, pricing, and revenue intelligence.
What changes after Einstein Labs.
Clearer roadmap decisions
Your roadmap becomes grounded in customer evidence, product usage, and business priorities.
Faster product execution
Specs become buildable, agent-ready, and connected to real product outcomes.
Better launch velocity
New features ship with product narratives, content, video, and measurement plans.
Stronger product learning
Usage data feeds back into the next roadmap decision.
AI-native monetization
Credits, usage, limits, entitlements, and billing become part of the product system.
Built for serious AI/SaaS teams.
Einstein Labs is best for founders and product teams that already have users, data, a codebase, or an urgent product bet. We work best when speed, judgment, and execution all matter.
- Seed to Series A AI/SaaS startups.
- Founder-led teams with fast decision cycles.
- Companies with customer interviews, support tickets, analytics, or roadmap ambiguity.
- Teams building AI products with usage, credit, or pricing complexity.
- Startups that need to ship faster without hiring a full product, engineering, analytics, and growth team.
Not for everyone.
Einstein Labs is not built for vague AI exploration, unpaid pilots, or teams that only want a generic dev shop. We work with teams that have urgency, access to product evidence, and a willingness to move quickly.
Built from real systems, not slideware.
Einstein Labs is built on working products across product intelligence, spec-driven software engineering, analytics, content, video, and monetization. The operating system exists because modern AI/SaaS teams need the full loop, not another disconnected tool.
Why we are building Einstein Labs.
AI has changed how software is built, but most companies still run product growth through disconnected workflows: research in one place, specs in another, code somewhere else, analytics after launch, and monetization as an afterthought.
Einstein Labs exists because the next generation of software companies will be smaller, faster, and more agent-native. They will not need separate teams for every part of the product loop. They will need systems that understand the customer, the product, the codebase, the launch, the usage data, and the revenue model together.
We are building that system from India and Singapore for the world.
— Abhishek Chatterjee, Einstein Labs · India & Singapore
Common questions.
Turn your next product bet into shipped, measured software.
Bring your customer evidence, product goals, and repo context. Einstein Labs will help you decide what to build, build it, launch it, measure it, and monetize it.