Custom AI development for your enterprise

There is no list price, and we would rather not quote one before we know what we are building. The platform is priced the way every other tier is, on your monthly visitor volume; the custom development is quoted on top of that once the scope is clear. You get both numbers in writing after the discovery call, before anything is committed.

Discovery usually happens within a week of an application, and the typical pilot runs about six weeks from kickoff to production. Whether the build starts straight after discovery depends on what is already in flight — we would rather give you the real date on the call than promise a start we cannot make.

Early on, very little: we are building and your people carry on as they are. What changes by the end is where the answers come from — anyone can ask a question directly and get it with the working shown, instead of waiting two days on an analyst. Work your team repeats by hand moves to something that runs on its own, one piece at a time, with a person still approving anything that leaves the building.

No, and that is rather the point. The endpoint sits over the tools you already run, and custom servers wrap your existing databases and internal APIs rather than replacing them. Nobody has to change how they work for this to pay off.

No. Everything we build speaks the Model Context Protocol, so Claude, GPT and Gemini reach the same tools. Use Claude today, switch to Gemini next year, run open models on your own hardware for sensitive work — nothing we built breaks. Connect your own model key and inference runs on your account rather than ours.

You keep everything: source code, documentation, and a team trained on the system. We design for our own obsolescence — the goal is that you extend it without us.

Both, and they are different jobs. Connecting a tool gives an agent a live query against a system that can answer one. Retrieval is for the material that cannot — contracts, policies, runbooks, internal schemas — which we chunk, embed and fetch at question time so an answer can cite the paragraph it came from. A custom RAG architecture is usually one part of an engagement rather than the whole of it, and we will say so if retrieval is not actually your problem.

Yes, and in anything else where the data cannot leave the building. We are not a vertical specialist and will not pretend to be: what we bring is the architecture that makes regulated data usable — the server inside your own perimeter, access rules per agent, human approval on anything that leaves, and an exportable audit log. If your procurement needs a named reference in your own sector before signing, we do not have one to give you.

No. We build the system around a model rather than the model itself: retrieval, tools, access rules, and routing between providers. That is where we have seen the answer quality actually come from, and it leaves you free to change model next year without rebuilding. If what you need is a trained or fine-tuned model of your own, we are the wrong shop and will tell you on the call.

Two answers, because there are two things. A custom MCP server we build for you runs inside your perimeter — your VPC, your own hardware — and we do not operate it or see what passes through it. The BusinessMCP platform is a different thing: it runs on Vercel with its database in Supabase’s EU region, it stores what it is for (analytics events up to 13 months, contacts, agent runs and tool calls), and every sub-processor is named with its location and purpose on the privacy page. Connect your own model key and inference goes to your account instead of ours. We would rather draw that line clearly than tell you we store nothing.

Yes, on Enterprise, per workspace in Settings. You can require two-factor authentication for every member — enforced against the session, so it holds however someone signed in — and restrict membership to your own email domains. You can also build access policies over 13 data classes and assign them to teammates or to individual API keys, so a contractor’s agent reads analytics and never revenue or contact details.

Part of it, yes. The gateway hardening we run in production — the SSRF guard that stops a user-supplied MCP server URL from reaching internal or cloud-metadata addresses, plus the upstream failure classification around it — is published under MIT at github.com/businessmcp/mcp-gateway, with the tests. The README walks through a real bypass we found in our own guard and the fix. The rest of the platform is closed, and we would rather say so plainly than claim more than we ship.

We do not place engineers into your team, take over a backlog, or do change-management consulting. An engagement is a scoped build with a handover date; anything outside that scope is a new scope, quoted separately. We also do not run your ad accounts or write your content.