Bigcircle does not place engineers. A voice agent in production is a latency budget spent across turn detection, transcription, reasoning, tool calls and speech, plus interruption handling and a record of every call. We have built voice agents in English, Hindi and Hinglish, and we deliver them as a studio engagement through our AI voice agents service.
Bigcircle does not place voice AI engineers. Our team builds the voice agent as a latency budget spent across turn detection, transcription, reasoning, tool calls and speech, with every call recorded and replayable. On an insurance voice build in English and Hindi, end-to-end response fell to around 900 milliseconds.
A voice AI engineer on a Bigcircle team keeps barge-in and turn-taking stable when every line is busy, in English, Hindi, and Hinglish, and grounds the call in live data through tools.
A transcript-correct call can still fail the caller, while the voice engineer on a Bigcircle team treats barge-in and turn-taking as part of the system that has to hold under load.
Realtime voice agents with interruption handling and a full record of every call, built by our team.
See what a production voice agent involves, what Bigcircle has built in English, Hindi and Hinglish, and the three ways to buy it.
Built by Bigcircle
End-to-end response fell from 2.5–3 seconds to around 900 milliseconds on noisy bilingual calls in English and Hindi.
Read the case study →Built by Bigcircle
The real-time loop, turn detection and interruption handling were ported intact from the insurance build, and the tool layer and data plane were rebuilt. Replies came back in under 1.2 seconds in English and under 1.3 seconds in Hindi and Hinglish.
Read the case study →Built by Bigcircle
The same voice runtime with a schema-driven scoring rubric on top, so a third domain cost a tool layer and a rubric rather than a new build.
Read the case study →Who builds it: Bigcircle's core team scopes the system and leads the build. Every engineer on that team cleared five stages of vetting and stays on one product.
Every engagement is a working system, built in your repositories under your IP by the team that scoped it. The three differ only in how much of the delivery we run.
We finish it
Your team built something that works in the demo and stalls on real inputs. We define what good means and build the eval set, route models for cost and latency, lock down the data path, and put a safety net under it before it takes traffic.
Best when you have a prototype that will not cross into production.
We build it
You bring the problem and we deliver the working AI system. Discovery, build, evals and deployment sit under one point of accountability, against a scope and price agreed before we start.
Best when the problem is clear and you want the result, not a team to manage.
We run it
A studio team of engineers and QA, led by our founder as your fractional CTO and architect, owns delivery on your AI roadmap. We run the build rhythm and make the hard technical calls; you bring the product context.
Best when you have a roadmap and no senior AI team to run it.
Choosing between the three is the engagement guide.
Every engineer on the core team that leads your system cleared these before joining. Each stage asks whether they can keep AI running once real customers are using it.
400 applicants
3%of applicants join
the team
What removes them
One real system, pressed hard. How much traffic did it take? What broke first? Who got the call when it did?
A working system with a bug hidden inside it. Anyone can build a demo in a weekend. Fixing code you have never seen is the actual job.
Before they write anything, they have to tell us how they would test it, and what they would do when it gets an answer wrong.
We give them a speed target and a budget, then ask them to explain the tradeoffs they made to hit both.
What do you do first? How do you find out what happened, undo it, and explain it to the customer in plain words?
No. Bigcircle does not place engineers or do staff augmentation. Bigcircle builds the voice agent as a studio engagement through its AI voice agents service, from the conversation design and the latency budget through grounding in live data to recording and scoring every call.
Bigcircle built an insurance voice agent where end-to-end response fell from 2.5 to 3 seconds to around 900 milliseconds on noisy bilingual calls, and a property discovery agent that reused the same real-time loop, with replies under 1.2 seconds in English and under 1.3 seconds in Hindi and Hinglish.
Bigcircle starts with a conversation about the calls the agent has to handle. You get a written scope covering what Bigcircle would build, in what order, and what it depends on from your side, then choose production hardening for a prototype you already have, a fixed-scope build at an agreed scope and price, or a studio-led programme led by our founder as fractional CTO. For voice, the build runs through designing the conversation, building for the latency budget, grounding it in live data, then recording and scoring every call. The work happens in your repositories, and you own the code.
Every engineer on Bigcircle's core team cleared five stages before joining, and the top 3% of applicants remain. Vetting starts from a system they already built, then breaks something and watches them fix it. For voice work the exercise breaks turn-taking so the agent talks over the caller, or leaves a call that cannot be replayed. They also 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. They lead client builds as a team.
Agents whose every action is checked before it runs and logged so it can be replayed, built by our team.
LLM features with a source behind every RAG answer and an eval that can fail the release, built by our team.
Model and prompt rollouts with a rollback, and traces a person on call can use, built by our team.
Bigcircle does not place engineers. Describe the system and what is in the way, and an engineer replies within two hours on weekdays. A written scope follows within a week.