AI Development Company

In India our AI builds start at ₹5 lakh. International projects are quoted in USD, and the three tiers above are where most of them land.

What moves the number, roughly in order of weight. How ready your data is — if the answers the AI needs are spread across PDFs, spreadsheets and somebody’s inbox, cleaning that up is real work, and it happens before a model is involved. How many systems it has to talk to, because every CRM, ERP, telephony or payment integration is its own small project. Whether the model is hosted or runs on your own servers, which changes the infrastructure work. And how much it will be used — usage is a running cost, not a one-time one.

We will not quote from a one-line brief. A short call is usually enough to put a real range on it, and if we think the use case is not worth building yet, we will say that instead of quoting it.

Yes. Both work, they just suit different situations.

Fixed price fits when you know what you want built — an agreed scope, one number, one date, and we carry the risk of estimating it right. A dedicated team fits when the scope is going to keep moving, or when you want to add engineers to a team you already have. You get named people working your hours, and the size changes month to month as the roadmap does.

A lot of clients do both: fixed price to get the first agent live, then a dedicated team once it is in production and the list of what is next stops getting shorter. Our engagement models and rates are on the Hire Developers page.

Yes, and usually without rebuilding it.

Most of what we ship sits alongside a system that already exists, through an API layer. The vendor onboarding agent above was added to a marketplace that was already live — sellers kept using the same signup screens, the agent just started filling them in. Your users notice a new capability, not a migration.

What we need is a way in: an API, a database we can read, or an export we can work from. If a system genuinely has no way in — an old desktop product, a vendor who will not open access — that is the constraint worth finding on day one, not in week three.

Four to twelve weeks depending on which tier above you are in, and yes — the first release goes to a limited group.

We put it in front of a small set of users or call flows, watch what people actually do with it, and widen from there. Our own front desk voice agent is still on that path: five hospitals, feedback still being collected, no wider rollout until it holds.

When an AI project runs late, it is almost never the model. It is waiting on access to data, or on someone internally who has to approve what the AI is allowed to say. Naming those two people at kickoff saves more time than any technical decision we make.

We are not tied to one, and the choice is driven by your constraints rather than our preference.

Hosted models — GPT-4o, Claude, Gemini — when you want the best available quality and the shortest path to launch. Open-weight models — Llama 3.3, Mistral, DeepSeek — when the data genuinely cannot leave your environment, or when volume makes per-request pricing the wrong shape. For voice we add speech models on top, so the agent can hold a call in English, Hindi or a regional language.

You get the pipeline code either way. That matters more than people expect: it means changing the model in a year is a configuration change, not a rebuild.

You own it, and no.

Your documents and prompts are not handed over for training. The vector database and embeddings live in your account, not ours. At handover you get the source code, the prompts, the pipeline and every account we created along the way, and the IP transfer is written into the agreement rather than promised on a call.

Which means you can take it to another team tomorrow. There is no licence to renew and nothing you have to keep paying us for to keep your own system switched on.

Encrypted in transit and at rest, access limited to the people actually on your project, and a log of who touched what.

Developers get repository and server access for their project only, and it is switched off at handover. Credentials live in a managed vault — never in the codebase, never in a chat thread. Our processes are ISO 9001:2015 certified, and an NDA is signed before the first real conversation, not after a contract.

Now the part most companies skip: we are not ISO 27001 certified. If your project needs a formally certified information-security standard, or obligations under India’s DPDP Act, or something sector-specific, tell us at kickoff and we will scope the work to meet it — rather than imply we already do.

It will, sometimes. So the real design question is what it is allowed to do when it is not sure.

We scope which decisions an agent makes on its own and which ones it hands to a person, and we build the handoff before the clever part. Our front desk voice agent answers reception questions and books appointments; it does not go near anything clinical. Every conversation is logged, so when something does go wrong you can read exactly what was asked and what it answered, and fix that case rather than guess.

Anyone who tells you their AI is never wrong is showing you a demo, not a production system.

Three things, and most quotes mention only the third.

Model usage. Hosted models charge per request, so a busy assistant costs more to run than a quiet one. Channel costs. A voice agent also pays for telephony minutes on top of the model. Upkeep. Providers retire model versions, prompts drift as your own data changes, and someone has to watch what the system is actually returning.

We quote all three separately and in writing before the build starts, rather than leaving them for you to find in month four. And if you would rather move it to your own team later, you can — you have the code and the prompts.

With the number you want to move, not the technology.

That is what our AI consulting engagement is for. We look at where your team’s hours actually go, which of those tasks a model can do reliably today, what data you already hold, and what each option would take to build. You get a shortlist ranked by effort against impact.

You also get a straight answer on the ones that are not worth doing yet — usually because the data is not there, or because a rule and a form would do the same job for a fraction of the money.

Ask any shortlisted company five things before you sign.

• Show me something of yours that is live. Not a demo video, not a prototype — something real users are on today.
• Who owns the data, the prompts and the trained model at handover? Ask for the clause, not a yes.
• Are the engineers in-house or subcontracted? Ask for names and where they sit.
• What will it cost to run each month? A quote without model usage in it is not a quote.
• What happens when it is wrong? If there is no answer, there is no plan.

We have answered all five on this page. Four of our builds are in front of real users, our 30 reviews were verified by Clutch rather than collected by us, and our processes are ISO 9001:2015 certified.