Clarify
“Our data is everywhere, and nowhere.”
ERP, business tools, spreadsheets, platforms: we connect what is scattered into a single, reliable view, without changing anything in your systems. Your teams ask their questions in plain language.
What we do
Four measurable results, from what you already have.
We don't sell you yet another platform. We start from your tools, databases and files as they are, and turn them into clarity, value, savings and time.
Leverage
“We have the data. We just don't use it.”
Incomplete records, history nobody ever uses, buried signals: we enrich with AI, we score, we simulate. Every recommendation is explained, and every figure states whether it is measured or estimated.
Save
“It costs us, but nobody sees it.”
Dead stock, leaking margins, oversized cloud, work done twice: we bring the costs nobody tracks into view, put a figure on them and set priorities.
Accelerate
“My teams spend their days copying and pasting.”
AI agents built into your tools take over the repetitive work: they read, cross-check and prepare, then leave the decision to you. Your teams get time back for what matters.
AI agents
One question, three systems, one verified answer.
Our agents do more than chat. They query your systems, cross-check sources, recalculate every figure before giving it to you, then bring up the screen you need. You confirm.
- Every calculation is run, never made up by the model.
- Measured, estimated or suggested: every figure carries its label.
- Can run offline, on a model installed on your premises.
Question
Why did the margin on the Atelier range drop this quarter?
→Reads the ERP · this quarter's orders, 12,480 lines0.8 s
→Cross-checks purchasing · prices from 3 suppliers1.1 s
→Queries logistics · 214 freight invoices0.6 s
✓Double-checks · independent recalculation, 0.1 pt difference0.4 s
Margin is down 4.1 points. 2.6 points come from a rise in brass prices at a single-source supplier, 1.2 points from express freight, now the norm at 3 branches. The rest is noise.
measured · margin, purchasingestimated · freight share
4 calculations · 2.9 s · no data changed
Foundations
We master the whole stack, from model to cloud.
AI ecosystems shift every month. We choose the right model, architecture and hosting for you, based on cost, quality and confidentiality.
Models
- Claude, Gemini, GPT
- Local, offline models
- Cost / quality trade-offs
- AI costs measured
Agents
- Agents that drive your tools
- Multi-agent orchestration
- Connectors and tools (MCP)
- Human in the loop
Data
- ERP, CRM, SQL databases
- APIs, feeds, files
- Read-only by default
- Quality and traceability
Cloud
- AWS, Azure, Google Cloud
- Continuous deployment
- Security, access, GDPR
- FinOps and efficiency
Method
A first tangible result in a few weeks.
No eighteen-month programme. We move in short stages, on your real data, and each stage stands on its own.
WEEKS 1 – 2
Assessment
What your data can tell you, what it can only estimate, and what it cannot tell you at all. Opportunities, quantified and ranked.
WEEKS 3 – 6
Working prototype on your data
A real tool, online and secure, that leadership uses first-hand. Assistant included.
THEN
Production
Connection to your systems, agents running continuously, gains measured week after week.
Every figure can be checked.What is estimated is labelled as estimated.
We break nothing.We add to what you have before replacing it.
People decide.Nothing goes into production without approval.
Security first.Protected access, no unnecessary personal data.
Training
AI training for your teams: no jargon, no smoke and mirrors.
We teach AI in higher education and train business leaders and teams. Stories, live demos, then practice on your own cases.
- Leaders: half a day to decide where to invest.
- Teams: one day to use the tools well.
- Schools: courses tailored to the curriculum.
programme · typical dayadaptable to your sector
09:00Seventy years of AI, told through archivesstory
10:30The fundamentals, without jargonlecture
11:30Seven years of models, compared side by sidedemo
14:00Frame a request, check the answerworkshop
16:30Lab: everyone tests on their own casespractice