Native artificial intelligence.

AI isn't a marketing gimmick. Done well, it replaces an entire team on certain tasks: sales qualification, document processing, brand-voice content generation, tier-1 customer support. We design quantified AI use cases, integrated into your existing tools (CRM, helpdesk, document base), with business safeguards, controlled costs, and GDPR compliance. Stack Anthropic Claude, OpenAI GPT-4o, open source models via Replicate or Together AI as needed.

Three pillars of AI that pays off

Qualified, scoped use case

No POC without ROI. We measure current task cost (team time × volume), AI cost (API + integration + maintenance), and define success metrics. AI only ships when ROI is proven.

RAG on your business data

Retrieval Augmented Generation: AI answers from your document base (internal processes, FAQ, client history, contracts), not from generalist web. pgvector or Pinecone embeddings, sourced citations, safeguards on sensitive topics.

Business safeguards and compliance

Locked system prompt, human validation on critical decisions, conversation logging, anonymization of personal data, documented GDPR compliance. AI doesn't drift, doesn't hallucinate out of context, doesn't make uncovered promises.

Typical use cases

Tier-1 customer support conversational agent

AI chatbot connected to your document base (FAQ, processes, contracts), able to answer 80% of common questions in French and English, with automatic human escalation if topic out of scope. Support cost divider 3 to 5x.

Inbound lead sales qualification

AI reads each inbound request, extracts key info (need, budget, timeline, company size), enriches with public sources, calculates priority score, assigns to right rep, drafts personalized first message. Rep validates and sends.

Brand-voice content generation

System prompt encoding your tone, values, signature phrases. AI produces blog posts, LinkedIn posts, product pages, sales emails sounding like your brand. Systematic human validation before publishing.

Document analysis and structured extraction

Legal, medical, real-estate firm processing heavy files. AI extracts key info (clauses, dates, amounts, commitments), generates structured summary, alerts on inconsistencies. Analysis time divider 5 to 10x.

What we deliver

›Qualified AI use case scoped with target ROI documented
›Integration with Claude Anthropic, OpenAI GPT-4o or Mistral as needed
›RAG on your document base with embeddings and sourced citations
›Business safeguards, human validation, GDPR logging and anonymization
›User interface integrated into your existing tools (CRM, helpdesk, back-office)
›Quality and cost monitoring (Helicone or LangSmith), drift alerts
›Quality follow-up, prompt tuning and continuous improvement

Tech stack

Claude (Anthropic) — Sonnet 4.6 and Opus 4.7 for reasoning
OpenAI — GPT-4o, GPT-4o-mini, text-embedding-3 embeddings
Vercel AI SDK — streaming, tool calling, multi-provider
Supabase + pgvector — embeddings and vector search
LangChain / LlamaIndex — RAG orchestration
Replicate / Together AI — open source models on demand
ElevenLabs / OpenAI TTS — voice synthesis
Whisper API — audio transcription
Mistral AI — European alternative for compliance
Helicone / LangSmith — cost and quality monitoring

Delivery method

Use case scoping and costing

Workshop with your teams to identify the task to automate. Measure of monthly volume, time consumed, acceptable error rate. Estimated API cost and target ROI.

Prototype and quality tests

Prototype on first real cases. Quality tests (accuracy, hallucination, cost per request, latency). Iteration on prompts, models, RAG. Metric validation.

Integration and safeguards

Integration into your existing tools (CRM, helpdesk, back-office). Implementation of safeguards: human validation, logging, GDPR anonymization, drift alerts.

Production and continuous improvement

Gradual rollout with real-time cost and quality monitoring. Monthly review of problematic conversations, prompt tuning, RAG document base updates.

Who it's for

Sales teams drowning in inbound email to qualify. Legal and medical firms processing heavy document loads requiring analysis. E-commerce operators wanting scalable multilingual support without hiring. Brands and agencies wanting to industrialize brand-voice content production. B2B companies wanting to automate inbound lead qualification with smart scoring.

Industries served

Legal and consulting firms (contract analysis, due diligence)
Medical and paramedical practices (patient file synthesis)
E-commerce and DTC (scalable multilingual support)
Brands and agencies (calibrated content generation)
B2B service companies (inbound lead qualification)
Real estate firms (lease and contract extraction)

Frequently asked questions

+Difference between ChatGPT off the shelf vs. custom integration?

Public ChatGPT is generalist, doesn't know your data, guarantees no confidentiality. Custom integration uses private APIs (Anthropic or OpenAI Enterprise), with your system prompt, your RAG document base, your conversational design, your business safeguards.

+Is my data fed to the public models?

No. Anthropic and OpenAI Enterprise APIs guarantee data isn't used to train public models. For critical cases we can use open source models hosted in Europe (Mistral, Together AI EU region) or self-hosted.

+What if AI hallucinates or errs?

Safeguards designed in: RAG with sourced citations, human validation on critical decisions, explicit refusal out of scope, logging for audit. Quality measured continuously, drift detected and corrected.

+GDPR compliant?

Yes: data minimization in API calls, pgsql anonymization before prompt, choice of European APIs (Mistral) or EU region for sensitive topics, documented processing register, access and deletion rights maintained.

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