Generative AI Integration Services

We design and build software that uses AI models to do a specific job for your business, such as answering customer questions, reading documents or carrying out routine tasks. That covers choosing the model, connecting it to your data and tools, testing its accuracy, and running it after launch. Most projects use existing models rather than training a new one from scratch.

We usually start with a small pilot on one real task, then decide together whether to build further. You get a date for the pilot and the full build with your quote, and a working demo every week. The timeline depends mostly on the state of your data and the number of systems involved.

If your team needs help writing, summarising or researching, a subscription to ChatGPT or Copilot is usually enough, and we will tell you so. Custom AI makes sense when it has to read from or write to your own systems, follow your rules, or handle data that needs tighter control.

We use provider plans whose terms say your data is not used for training, limit what the AI can see by role, and log what it does. When data must not leave your control, we can host an open model on your own server or cloud account. We go through these choices with you before the build starts.

AI models can be wrong, so we design for it. Answers are drawn from your own content with sources shown, we test on a set of your real questions before launch, and anything uncertain or costly goes to a person. After launch, conversations are logged so mistakes can be found and fixed.

We work with models from OpenAI, Anthropic and Google, and with open models that can be hosted on your own server. We choose by accuracy on your task, running cost and where your data is allowed to go, and we build so the model can be changed later without rebuilding the system.

Yes, and it is often the best place to start. We connect AI to your current software through APIs, so features such as summaries, drafting, smart search or an assistant appear in the screens your team already uses. Nothing needs to be rebuilt unless you want it to be.

You do. The code, prompts and your data are yours. The system runs on your own server or cloud account, and the accounts with AI providers can be in your name, so you are not tied to us to keep it running.

Yes. AI systems need attention after launch, because your content changes, models get updated and real users ask things no one expected. We watch quality and costs, fix problems and improve answers from real use, under a maintenance quote kept separate from the build.

MCP, the Model Context Protocol, is an open standard that lets AI assistants such as Claude and ChatGPT use outside tools and data. You need an MCP server when you want those assistants to work with your own CRM, database or product. We build them with sign-in, permissions and logging. If your AI only lives inside one app of yours, a direct integration is often simpler, and we will say so.

A focused first AI project with CodingCafe starts at ₹50,000. Larger builds cost more, depending on how clean your data is, how many systems the AI connects to and how accurate it needs to be. We give you a fixed quote after a free call, before any work begins. AI model usage, hosting and maintenance are shown separately, so you can see what it costs to build and what it costs to run.