Offshore AI Development / Chennai, India
Offshore AI development in India, built for US companies.
Senior engineers in Chennai who work your hours, ship in weeks, and hand you full ownership of everything they build. You get the talent and the live collaboration of a US team at roughly half the cost.
- ~50–70%
- lower than US rates
- 9+ hrs
- daily US overlap
- 100%
- IP ownership
- Weeks
- to first build
The collaboration story
Your workday and ours genuinely overlap.
The usual offshore complaint is the 12-hour wall: you write a question, you get an answer tomorrow. We run our schedule against US time zones, so the bulk of your business day has live engineers on the other side.
Hours shown in 24h US Eastern time. Standups, code reviews, and pair sessions land inside the highlighted window, every working day.
Why US teams choose this
Offshore without the usual trade-offs.
9+ hours of US-hours overlap
Our day starts before yours ends and runs deep into your morning. Standups, reviews, and pair sessions happen live, not over a 24-hour email relay.
100% IP ownership and signed NDAs
Every line of code, model weight, and prompt belongs to you from day one. Mutual NDAs and clean IP assignment are standard, not an upsell.
Senior, English-fluent engineers
You work directly with the people writing the code. Fluent communication, US-context product sense, and the seniority to push back when it matters.
Shipping in weeks, not months
Small senior teams skip the layers. A working prototype in a few weeks, then tight iteration loops against real usage instead of a year-long roadmap.
Honest comparison
In-house US hire vs typical offshore vs FoundrySoft.
Offshore done badly earns its reputation. Here is where we sit against both an expensive local hire and the cut-rate shops that gave the category a bad name.
| Metric | In-house US hire | Typical offshore | FoundrySoft |
|---|---|---|---|
| Loaded cost per engineer | $180k–$250k / yr | Low, but variable | ~50–70% less than US |
| Time to a working build | Hiring first: months | Slow, hand-off heavy | Weeks |
| US-hours overlap | Full | 1–3 hours, if any | 9+ hours, live |
| Communication | Direct | Through a PM layer | Direct with engineers |
| IP ownership | Yours | Often murky | 100% yours, in writing |
| Seniority | What you can afford | Mixed, often junior | Senior by default |
Ranges reflect typical fully loaded engineering economics, not a specific quote. Yours depends on scope.
What we build
AI work, end to end.
LLM products and agents
RAG pipelines, agentic workflows, evals, and the unglamorous plumbing that keeps a model reliable in production: retries, guardrails, caching, and cost control.
AI features in existing apps
Drop intelligence into the product you already have. Search, summarization, copilots, and classification wired into your stack without a rewrite.
Data and model infrastructure
Vector stores, fine-tuning loops, inference deployment, and observability so you can see exactly what your AI is doing and what it costs.
Full-stack delivery
Frontend, backend, and infra under one roof. The same team that builds the model serves it, so nothing falls between the cracks at the seams.
Let's scope your AI build.
Tell us what you are trying to ship. We will come back with a direct read on approach, timeline, and cost, with the engineers who would actually do the work on the call.