AI agents that answer, call and act on behalf of your team.
Chatbots and calling agents that actually do the work.
Most AI demos fall over on the second question. We build the version that survives a real customer: chatbots that answer from your documents, prices and policies rather than the open internet, voice agents that take bookings, qualify leads and follow up on payments over an actual phone call, and back-office assistants that read, summarise and route the paperwork that eats your day.
- EN · HIcalls handled in both languages
- 100%of conversations logged
- Hand-offto a human when it matters
Built around how the work really flows.
Every deployment starts with your data and your rules. We ground models with retrieval over your own content, add human hand-off where the stakes are high, and log every conversation so you can see exactly what the AI said and why. It ships as part of your existing system, on WhatsApp, on your website, in your CRM or on a phone line, not as another tab.
Production-grade generative AI: customer chatbots grounded in your own data, voice agents that make and take calls, and assistants that draft, classify and file so your team doesn't have to. Built on your knowledge, guard-railed, and measured against real conversations.
What we build into it
- Customer chatbots grounded in your own data (RAG)
- Voice and calling agents for bookings, follow-ups and support
- Document, email and ticket automation with human hand-off
- Evaluation, guard-rails and full conversation logs
Who this is for
Typical stack
Four ones. Zero theatre.
One hour to reply, one day to blueprint, one week to prototype, one month to ship. Every generative ai solutions engagement starts in this shape.
- IWithin the hour
A real person reads your note.
The engineers who will build it are the ones who reply. No forms routing to forms.
- IIWithin the day
We sketch the system out loud.
A short conversation and a one-page blueprint of what we think you actually need.
- IIIWithin the week
Something you can touch.
A working prototype, not a Figma file. Your team presses the buttons and we adjust.
- IVWithin the month
Live. Quietly.
First version in production, your team has the keys, and we are still on Slack.
Before you get in touch.
Can the chatbot answer from our own documents and pricing?
Yes. We build retrieval-augmented assistants that answer only from the content you give them: manuals, price lists, policies, past tickets. When the answer isn't there, the bot says so and hands off to a person instead of guessing.
What can an AI calling agent actually do?
Make and receive real phone calls in English and Hindi: confirm bookings, qualify inbound leads, chase pending payments, run reminder and feedback calls, and book a callback with a human when the conversation needs one. Every call is transcribed and logged into your CRM.
How do you keep the AI from saying something wrong?
Grounding, guard-rails and evaluation. Answers are constrained to your data, sensitive actions require confirmation or a human, and we test against a suite of real conversations before launch and after every change. You can see every exchange in the logs.
Which models do you use, and can we keep our data private?
We work with Anthropic Claude, OpenAI and open-weight models, and choose per use case on quality, cost and data-residency needs. Your data stays in your own infrastructure or region where required, and we never train models on it.
Tell us the messy version first.
You don't need a perfect brief. Tell us the problem in your own words and we'll figure out the shape of the project together.