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.”
Bigcircle assigns engineers who have already been through a break-and-fix vetting, and publishes the delivery status of the systems behind the work.
See how an engineer is matched to a product, how the five stages work, and which case studies are in production versus built and not deployed.
Bigcircle builds production agents, retrieval, document intelligence, and voice, and guardrails return a verdict before an action reaches your systems. Engineers stay on one product, and the five vetting stages start from a system they built and a break we watch them fix. When a run fans out to many agents, Jev is the decision layer, and code merges a return only after the verification gate passes.
Bigcircle is an AI engineering company that hires and trains its own engineers, keeps each one on a single product, and does not subcontract the work.
A services setup that splits engineers across three or four accounts leaves nobody to see a whole system through, while Bigcircle keeps each engineer on one product from start to finish.
Tirth Gajjar, Founder & CTO
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.
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.
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.
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.
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.
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.
Bigcircle provides them. Tirth Gajjar, the founder and CTO, hired every engineer and trained them the same way, for depth in one or two areas and enough breadth to follow a problem across the stack. There is no bench, no rotation between accounts, and no subcontracting.
You embed an engineer, take a CTO-led pod, or buy a fixed-scope build. On an embed you set priorities and own the code, and Bigcircle handles employment. The pod is led by the founder, and Bigcircle owns the delivery rhythm and the hard technical calls. A fixed-scope build is discovery, build, evals, and deployment against a fixed scope and price. Most clients see a shortlist within two to five business days, after a call about the AI problem, the stack, and the seniority you need.
Every engineer Bigcircle presents has cleared five stages. Bigcircle starts with a system they already built, then breaks something and watches them fix it. They say how they would know it is working, how they would make it fast without running up the bill, and what they do first when it is late and the AI got it wrong. Historically fewer than three in a hundred applicants make it through.
Email hello@bigcircle.ai or use the contact page, and say what you are trying to ship. A fixed-scope build ships against a fixed scope and price. An embed or a CTO-led pod is scoped on a call about the problem, the stack, and the seniority you need. Bigcircle replies within two hours on weekdays.
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.