AI Solutions & Integrations
We integrate AI where it actually adds value — especially on top of data. Scraping + LLM pipelines that extract structured insight from unstructured content, RAG systems that make your internal data queryable, document processing with OCR and NLP, and custom AI workflows. No buzzwords, just practical implementations.
RAG · OCR · NLP
Conçu pour la production.
AI projects fail when they start with a model instead of a workflow. We anchor on the business step you want to remove — classifying tickets, extracting fields from PDFs, answering internal questions — then choose retrieval, fine-tuning, or prompt chains that fit your data and budget.
Our sweet spot is AI on top of data you already collect: scraped pages, uploaded documents, support history, product catalogs. That is where RAG, structured extraction, and guardrails compound value instead of producing demos that never ship.
We ship with evaluation in mind: golden datasets, regression tests on prompts, cost caps, and human-in-the-loop paths when confidence is low. Production means measurable accuracy, not a flashy chat bubble.
Cas d’usage, en production.
LLMs, RAG pipelines, document extraction, and AI-powered data workflows. Practical implementations that save time and money.
LLM-Powered Data Extraction
Feed scraped or uploaded content into LLM pipelines to extract structured data. Product specs from HTML, key clauses from contracts, entities from news articles — all normalized and ready to use.
RAG & Internal Knowledge Bases
Make your internal documents, support history, or product catalog queryable with natural language. Vector search + LLM retrieval that actually returns accurate answers.
Document Processing & OCR
Feed in contracts, receipts, or forms. Get structured data back. OCR, classification, and entity extraction working together in one pipeline.
Customer Support & Automation Bots
AI-powered chatbots that handle common questions, route complex issues to your team, and learn from past conversations. Integrate with WhatsApp, Slack, or your own UI.
Sales & support copilots
Assist reps with account context, past threads, and product docs — grounded answers with citations, not hallucinated policies.
Content moderation & classification
Route user-generated content through classifiers with escalation rules, audit trails, and periodic model refresh as patterns shift.
De la découverte au transfert.
Un chemin clair, avec des jalons sur lesquels vous pouvez vous appuyer : pas de boîte noire, pas de dérive de périmètre à la fin.
Define success
We agree on accuracy targets, latency, and cost per transaction before choosing models or architecture.
Build eval set
Representative examples from your data — including messy edge cases — become the benchmark for every iteration.
Ship guarded MVP
Limited users, logging, fallbacks, and kill switches. Expand traffic as metrics hold.
Improve in production
Feedback loops, prompt/version control, and optional fine-tuning when volume justifies it.
Ce que nous livrons.
Ce que vous recevez.
Des résultats tangibles à la fin de chaque mission : du code, de la documentation et des systèmes exploitables par votre équipe.
- Architecture doc (models, stores, APIs)
- Prompt/version registry or config
- Evaluation harness & baseline metrics
- Deployed API or embedded UI component
- Cost & usage monitoring
- Security review for data residency & PII
Questions fréquentes.
Do you fine-tune or only use APIs?
We default to strong base models plus RAG and tooling. Fine-tuning is an option when you have enough labeled data and a stable task definition.
How do you reduce hallucinations?
Retrieval with citations, structured outputs, confidence thresholds, and refusing when context is insufficient — tested against your eval set.
Can this run in our VPC?
Yes. We can deploy open models or route to enterprise API agreements depending on compliance needs.
Explorer la stack.
Prêt à commencer ?
Parlez-nous de votre projet et nous trouverons la meilleure façon de vous aider.