Your repetitive tasks. Automated.
Extraction, sorting, summaries, routing: your processes run on their own, continuously — no fatigue, no forgetting, no double entry.
01
What we automate
Every company has repetitive tasks: re-entering data from one tool into another, processing invoices, writing the same summaries over and over, sorting emails, assembling reports. We design custom-built systems around your exact processes — not generic workflows bent into shape.
Document processing
Invoices, contracts, quotes — automatic extraction, verification and filing.
Internal AI agents
Assistants that answer your team's questions from your own documentation.
Complete workflows
From incoming request to resolution, with human approval where it matters.
Data enrichment
Automatic cleaning and enrichment of your customer or product data.
Monitoring & summaries
Competitive watch, weekly reports generated and sent automatically.
Tool integrations
Making your CRM, ERP, email, forms and files actually talk to each other.
02
Concrete examples
Three real contexts, three different solutions — and results measured before being announced.
Accounting firm
- Contexte
- 30 invoices per day entered by hand by the team.
- Solution
- OCR pipeline + LLM extraction + final human review on sensitive cases.
- Résultat
- −80% data entry time · ROI in 4 months
03
Our approach
From audit to supervision: an automation must be as dependable as an employee.
Process audit
Together we identify high-impact tasks and quantify the expected gain before writing a single line of code. If automation is not profitable for you, we tell you.
Fast prototype
A first working version within weeks, validated on your real cases — not on slides.
Industrialization
Reliability, monitoring, error handling, traceability: going from a demo to a system you can depend on every day.
Humans in control
Sensitive cases require approval, edge cases get reviewed, numbers and alerts are always available. The AI prepares, your team decides.
04
Custom, not forced no-code
Generic platforms (Zapier, Make, n8n) are great to get started — we use them ourselves when it makes sense. But as soon as a workflow becomes complex, high-volume or strategic, a custom-built automation costs less in the long run and does exactly what you need. Our guide « [AI automation: custom or no-code?](/guides/automatisation-ia-custom-vs-no-code) » details when to choose which.
05
Technologies
- LLMs via API (OpenAI, Anthropic, Mistral…) — with the option to self-host open models for confidentiality
- Self-hosted n8n for orchestration when no-code is enough, custom code beyond that
- Python and TypeScript for specific processing
- Vector databases and RAG to query your internal documents
- PostgreSQL for data — everything can live on your infrastructure
Your data stays under your control: hosting in France or Europe, no sensitive data sent to third parties without validation, full traceability of AI processing.
Frequently Asked Questions
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