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AI Integration: OpenAI and Claude

Language models have become software components like any other: an API, a cost per call, use cases where they excel and others where they get it wrong. We integrate them where they bring measurable value, with the necessary guardrails, on your data and inside your tools, always starting with a short proof of concept.

Describe my project

What we do

01

RAG chatbots over your documents

An assistant that answers from your documentation, procedures or catalogue, citing its sources: vector search, verifiable answers, no invention.

02

Extraction and classification

Invoices, quotes, emails, résumés, forms: structured data extraction, automatic sorting, human review on uncertain cases.

03

Automations and agents

Workflows that read, decide and act: lead qualification, draft writing, meeting summaries, connected to your CRM, Slack or ERP through n8n or code.

04

AI inside your products

AI features in your web or mobile application: suggestions, summaries, semantic search, with streaming, caching and cost tracking.

Where to start

AI projects that succeed start with a precise use case and a measurable gain: cut support ticket handling time, extract data from 500 invoices a month, let the team query 300 pages of procedures. We scope that case, build a proof of concept in 2 to 3 weeks on your real data, measure, then decide together whether to industrialise.

What a production integration includes

A document ingestion pipeline, a vector database, versioned prompts, an evaluation set, error handling and rate limits, per-use cost tracking, and a web interface for users or a connection to their existing tools. All of it documented and maintained, like any other software, whether it runs on a Node.js back-end or in Python.

Stack & tools

  • OpenAI API
  • Anthropic Claude
  • Mistral
  • embeddings
  • pgvector
  • LangChain
  • Vercel AI SDK
  • n8n
  • Node.js
  • Python

Why ELDEV
OpenAI and Claude

We are developers before we are 'AI experts': we know how to integrate a model into a real architecture, with a vector database, job queues, error handling and cost tracking. We choose OpenAI, Claude or an open-source model according to your data and budget constraints, document the flows for your GDPR compliance, and measure answer quality before going to production.

Frequently asked questions

OpenAI, Claude or an open-source model?
OpenAI and Claude for quality and simplicity, with API modes that do not use your data for training. A self-hosted open-source model (Mistral, Llama) when data is highly sensitive or volumes are very high, on infrastructure we can manage for you. We assess this together at scoping.
Is my data protected?
Yes, if the architecture is right: pseudonymised data where possible, APIs without retraining, European hosting, access logging. We document every processing step for your GDPR register. See our artificial intelligence page.
How much does an AI integration cost?
Development depends on the use case; API costs come on top and vary with volume. We start with a 2 to 3 week proof of concept to validate the value before committing further. Describe your need, reply within 12 hours.
How do you stop the AI from making things up?
By constraining it: answers grounded in retrieved documents (RAG) with citations, structured and validated output formats, confidence thresholds with hand-off to a human, and test sets that measure quality before every change.

Related service: Artificial Intelligence

A project, an outage, a question?

Describe your need in a few lines. Free scoping, reply within 12 business hours, and a single point of contact from the first exchange to launch.

Describe my projectcontact@eldev.fr