Most small businesses do not need another AI tool. They need the AI they already pay for to see their customers, orders and documents, and to act on them safely. That is what AI integration is: connecting a large language model to the systems you already run, with permissions you control and a log of everything it does.
What AI integration services include
AI integration services connect a language model such as Claude or ChatGPT to your business software, so it can read and update real data instead of answering from general knowledge. The work covers the connector itself, access control, logging, and testing against your real workflows.
In practice, a project usually includes:
- A map of the systems and the questions. Which data the AI needs, which actions it may take, and who approves them.
- A connector, most often a custom MCP server (Model Context Protocol, the open standard that Claude, ChatGPT and other assistants use to call external tools), or a direct API integration when an assistant is not involved.
- Authentication and scoped permissions. API keys or OAuth 2.1, one identity per user, read-only by default, write access only where it is needed.
- Guardrails on dangerous actions. Deletion, payments and outgoing emails are either excluded or routed to a human for approval.
- Logging. Every call the AI makes is recorded: who, what, when, with which result.
- Tests. Automated tests on each tool, plus acceptance tests on your real scenarios before launch.
Claude or ChatGPT
The assistant your team already uses.
MCP server
Authentication, scoped permissions, no risky actions.
Log
Every call recorded: who, what, when, result.
Your systems
CRM, ERP, files and databases, read-only by default.
MCP servers we have built and run in production
We do not describe MCP from a slide deck. These are servers we built and operate:
| Server | What it connects | Tools | Safeguards |
|---|---|---|---|
| Compliance SaaS for training providers (our product, kaliio.fr) | Courses, sessions, trainers, clients, documents | 27 read and write tools, usable from Claude and ChatGPT | API key or OAuth 2.1; no deletion and no outgoing email through the AI |
| Second SaaS product (kaliopi.io) | Same domain, separate product and data | Ported from the first server | Same model |
| French legal research server | Official French legislation and case-law APIs, plus company and tax bulletins | 9 search and read tools | Token-protected; public data only |
| Internal ERP | Clients, quotes, invoices, pipeline | Authenticated REST API used by Claude | Payment matching is proposed, never validated by the AI |
The legal server started from an open-source MCP project, which we extended with two more official data sources and deployed as a hosted connector. Reusing solid open-source work where it exists is part of keeping integration costs down.
How much does it cost for AI integration?
The cost of an AI integration depends mainly on how many systems you connect and whether the AI only reads data or is allowed to write it. A read-only connector to one well-documented API is a small project; write access to several systems with approval steps is a larger one.
What we quote, line by line:
| Cost driver | Smaller scope | Larger scope |
|---|---|---|
| Systems connected | One CRM or one database | CRM + ERP + file storage |
| Access | Read-only | Read and write, with approvals |
| API quality | Modern REST API with docs | Legacy system, exports, screen data |
| Users | One shared service account | Per-user identity (OAuth) and audit |
| Hosting | Serverless function | Dedicated service with monitoring |
For full agent budgets (build, run and maintenance), see our AI agent cost guide.
Which AI is best for integration?
The best AI for integration is the one your team already uses, as long as it supports a standard connector protocol. Claude and ChatGPT both support MCP, so a well-built MCP server works with either and you are not locked into one vendor.
Our own default is Claude for agent work that involves long documents and multi-step tool use, and we pick smaller, cheaper models for routine steps such as classification or extraction. The integration layer stays the same when you switch models. If you are deciding where to start, our guide to Claude for small business compares the options for a small team.
What are the top 5 AI services?
For a small or mid-sized business, the five AI services that matter most are: AI strategy and readiness, AI integration with existing systems, custom AI agents, AI-assisted software development, and ongoing monitoring and maintenance. Integration is the one that decides whether the others deliver anything.
Integration rather than another tool
Every new SaaS tool adds a login, a subscription and a copy of your data. An integration works the other way: the AI comes to the systems you already run. Where those systems are missing or outdated, we build what is needed (see custom software). For regulated work, the same approach applies to private sources: our law firm page shows how an AI connects to official legal databases.
How a project runs
- A 30-minute call to understand your systems and the first use case.
- A short written scope: data, actions, permissions, approvals.
- A working connector on a test environment within the first sprint, tested with your real questions.
- Production launch with logging and monitoring, then a monthly plan if you want us to maintain it.