About Bigcircle

Bigcircle is an AI engineering company. Our engineers build production AI systems (agents, retrieval, document intelligence, voice), and they stay on one product from start to finish instead of being split across several accounts at once.

“You have changed how I think about Indian developers.”
Said to Tirth by colleagues and clients in the US and Europe, over several years, and meant as praise. He heard it often enough to start asking why it needed saying.

Teams that ship with us.

  • Nurix
  • Solarpunk
  • Indexa Exchange
  • Toast Studios
  • Gartner
  • Blueland
  • inkbolt

Why we started

Tirth Gajjar, Founder & CTO

  1. What I kept hearing

    People meant it well. But I had worked alongside plenty of Indian engineers who were just as capable and had never been described that way. So the compliment was really a statement about what people had come to expect, and the expectation was not coming from nowhere.

  2. How most service companies are set up

    A services business makes its margin on utilization. So engineers get split across three or four accounts at once, tracked in billable hours rather than outcomes, and kept on whatever stack the account already runs, because moving them to a new one costs money. So nobody sees a whole system through, nobody has time to learn a new one, and the same mistakes ship for years. Then people look at the output and draw conclusions about the engineers rather than the setup.

  3. What we do instead

    I hired every engineer at Bigcircle myself and trained them the same way, and they stay on one product long enough to understand it properly. It grows slowly and it does not scale by adding seats, which is why most companies do not work this way. It also means price is not the main thing to judge us on. The systems we have built are listed further down this page.

How the team is built

The team01

Every engineer was hired and trained here

No bench, no rotation between accounts, no subcontracting. Each engineer was selected individually and brought up on the same practices, which is why the work is consistent from one project to the next instead of varying with whoever happened to be free.

The shape02

Depth in one or two areas, breadth across the rest

Each engineer goes deep enough to own a hard problem, wide enough to follow it across the stack, and knows enough about the product to question a spec rather than just build what it says. T-shaped, if you want the shorthand.

Why it matters now03

AI work crosses too many areas to hand off

Shipping an AI feature means weighing retrieval quality, evaluation, latency, cost and failure handling against each other, usually at the same time. Split across specialists, those trade-offs get passed back and forth and take a long time to resolve. An engineer who understands all of it can settle them directly.

Who we are

Tirth Gajjar

Founder & CTO

Founder and CTO of Bigcircle. He hires and trains the engineering team, leads the production AI work, and writes the guides on this site.

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Let's build something that ships.

Tell us what you're building. We'll tell you whether you need an engineer embedded or the whole build led, what's achievable, and where the real bottlenecks are.

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