Integration of an artificial intelligence API
The model only has value if it writes into your tools
We integrate a language model, a voice or a transcript into the CRM, the calendar, the file. Consumption budget, data hosting, fallback path: a chat demo is not a connector.
- AI connectors in production
- business tools wired
- budget and residency scoped
What is an artificial intelligence API and when should you have it integrated?
An artificial intelligence API exposes a model (text, voice, image, video) that your application calls to produce an answer, audio or a transcription. It is not a magic “AI layer”: it is a connector, with authentication, quotas, latency and cost per call. You have it built when the model must write into your CRM, calendar or telephony, when sovereignty requires hosting in France, or when the voice must stay under a spend cap. For enterprise integration advice, our expertise pages remain the right place; here we talk about the technical wiring.
The AI APIs we wire
Agent vocal IA
An AI phone system wired into your telephony, calendar and CRM.
Gemini
The Gemini API, for text and multimodal in your application.
Mistral
An LLM when sovereignty and hosting in France weigh on the choice.
HeyGen
The video avatar, for a journey where generated video is a deliverable, not a gadget.
ElevenLabs
Speech synthesis and framed voice cloning, with cache and cost cap.
Transcription
Speech-to-text (Whisper, Deepgram and equivalents) pushed into your files.
Anthropic (Claude)
Tool use and MCP, to expose your business tools to the model.
OpenAI
The Responses API, structured outputs and real time.
Cursor
Your developers' editor, wired to your internal tools.
The demo works. Production is a different story.
The model answers. Until it writes somewhere, cost is capped and residency is a criterion, it is only a prototype.
The prototype works, the bill explodes in production
Cache, spend cap, replaceable model. Every call has a tracked cost, not a surprise at month end.
The voice agent answers, but writes nowhere
The call creates the appointment, the record, the ticket. Without a business tool behind it, it is just an expensive answering machine.
We cannot host this outside France
We scope the provider (Mistral and sovereign options) and data transit. The constraint becomes a selection criterion, not a legal surprise.
The transcription arrives, nobody uses it
The text feeds a report, a ticket, a file. An audio queue with no destination is a cost, not a feature.
What each AI API actually involves
Agent vocal IA
Telephony + LLMThis is not a brand, it is an assembly: telephony, voice, model, business tools. We build it and wire it into your switchboard, calendar and CRM. Latency and cost are measured per call. Handoff to a human is a nominal case, not a failure. It is the most sellable use case in the category.
- Telephony, voice and model assembled
- Writes into the calendar and CRM
- Latency and cost measured per call
Anthropic (Claude)
Claude APIThe model that goes furthest on long documents and on tool calling, with MCP as the exposure standard. The point to settle early is location: the direct API offers no European region, EU residency goes through Bedrock or Vertex, which changes authentication and quotas.
- Tool use and MCP as standard
- Prompt caching on large files
- EU residency through a host
Cursor
Dev toolingHere the integration is not about a product API but about your development chain: exposing ticketing, the database schema and internal documentation to the editor through MCP, writing your conventions as versioned rules, and governing access at team level.
- MCP servers on your internal tools
- Repo conventions versioned
- Governed access, not tolerated
ElevenLabs
AI voiceFrench speech synthesis, framed cloning, sometimes transcription. The cache avoids resynthesising the same text. The engine stays replaceable. Cloning is done by the rules: consent, usage, retention. That is already documented on the tool page.
- French voice in the product
- Cache and spend cap
- Framed cloning, not improvised
Gemini
Gemini APIA model API to wire into a product journey (assistant, extraction, classification). No invented routes here: scoping fixes the model, optional multimodal, the token cap and where the answer is written. This is not a “Gemini agency” page.
- Model call in the journey
- Token cap
- Answer written into the business
HeyGen
Video avatarA generated video avatar, relevant when video is a deliverable (training, communication, personalisation). No invented quotas: scoping fixes volume, language, image rights and where the video is stored. A demo gadget is not an integration.
- Video in a real journey
- Image rights scoped
- Storage and cost per render
Mistral
Sovereign LLMThe sovereignty lever: useful for SMEs and the public sector when data must not leave. The API and hosting options are confirmed at scoping. The connector isolates the provider, so it stays replaceable if the legal constraint moves.
- Sovereignty angle scoped
- Provider isolated
- Data and transit discussed before the code
OpenAI
OpenAI APIThe best-tooled ecosystem, with structured outputs and built-in real-time voice. Two deadlines to know: the Assistants API sunsets on 26 August 2026, and European residency is chosen when the project is created, with no conversion afterwards.
- Reliable structured outputs
- Built-in real time
- Europe project from creation
Transcription
Speech-to-textSpeech-to-text for reports, tickets, operational subtitles. Whisper, Deepgram or equivalent: scoping fixes language, delay, destination of the text. An audio queue with no write into the file is not a deliverable.
- Audio to text in the business
- Language and delay scoped
- No dead-letter queue
Four wirings into the SI, not a chat
Voice agent that writes the appointment
The call creates the slot and the record. Without a calendar or CRM behind it, it is an expensive answering machine.
Extraction into the file
Classification, fields, documents. The model feeds the business, it does not stay in a transcript.
TTS in a business journey
Scoped TTS, identity, cost per minute. A jingle is not a connector.
Transcript pushed into the tool
Audio becomes a searchable object. Nobody listens to 40 minutes to find a decision.
Product, legal, finance, ops: the model is replaceable
This page is not the AI agency offer. We wire a model to your tools, with a budget and a fallback.
Product treats AI as a step
Input, output, file. Not a magic conversation in the middle of the journey.
Legal sets residency
France, EU, or not. This is not a badge. We decide it before the vendor.
Finance caps tokens
Cost is designed. Cache, cap, smaller fallback model. Not a bill discovered later.
Ops have a fallback when the model fails
Timeout, hallucination, quota. A human queue or a rule. The demo has no such path.
A voice AI agent in production, not a prototype
The method an AI API forces
Business wiring
Tools read, tools written, input / output format.
Deliverable: wiring mapToken budget
Cap, cache, fallback model, drift alert.
Deliverable: budget per journeyData residency
Region, logs, subprocessors, what does not leave.
Deliverable: residency sheetEval and fallback
Eval sets, thresholds, human or rule fallback queue.
Deliverable: eval bench and fallbackWhat nobody tells you before you sign
A model without a business tool is a demo
If the answer writes nowhere, you bought a conversation. Scoping starts with the calendar, CRM, ticket, not with the prompt.
Cost is designed, it is not observed afterwards
Without cache or cap, the bill follows success. Observability of the token or the audio second is part of the connector.
Sovereignty is not a marketing badge
Hosting, subprocessors, logs: we list them. “Sovereign AI” without scoped transit does not hold an audit.
This page is not the AI agency offer
Enterprise integration advice lives on our expertise pages. Here we wire an API. The two complement each other, they are not duplicated.
What AI is measured to save, and what we measure for you
Artificial intelligence API: your questions
Three steps. First freeze the journey: which input, which output in the business (field, ticket, call), which cost cap. Then isolate the provider behind an interface, with cache, secrets and observability. Finally test latency, failure and degradation. The difficulty is not getting an API key, it is making the model write in the right place, at the right price. For Claude, OpenAI or MCP, see our matching stack pages.
This page targets wiring an API (voice, LLM, transcription) into a product. The enterprise advice and rollout offer is already carried by our AI integration, generative AI and agents expertise pages. We do not recreate “AI agency” or “enterprise AI integration” queries here. If your need is programme scoping, start with the expertise pages. If your need is a connector, stay here.
Gemini is often the right volume / difficulty ratio when you want multimodal in the application. Mistral becomes the priority when sovereignty and hosting weigh. Both hide behind the same interface in the connector. The choice is settled on data and contract, not on the benchmark of the moment. Claude and GPT stay on the stack pages, so we do not compete against our own URLs.
A classification call in a file costs far less than a voice agent wired into telephony. Connector cost and model usage cost are two lines. We scope both, with a cap, before starting. A demo without observability is not a quote.
Yes, if the business does not talk to the provider SDK. We set an interface (messages, tools, voice) and we keep the provider behind it. Changing voice or LLM remains a configuration and test change, not a CRM rewrite. That is a scoping decision, not a late-project refinement.
Which tool must the model write into?
30 minutes to list CRM, calendar, file, the token budget and the residency constraint. This is not an AI-agency scoping call.
Discuss my AI API project