Offering

Our AI & Data offering

From the principle of engagement to industrialization, a method that combines consulting and data.

Four principles of engagement

1

Business-first proposition

NLP starts from the business opportunity, never from technical capability. No "data for the sake of data".

2

Concrete business cases

NLP reasons in direct, measurable benefits: revenue, cost, profitability, compliance. Fast and demonstrated ROI.

3

Value upstream

NLP positions itself early, on proofs of concept, with functional demonstrators (ideally MVPs).

4

Partner to your Labs

NLP complements and strengthens your internal AI teams rather than competing with them.

A joint method: Consulting & Data

Two streams run in parallel, up to a supported GO / NO GO decision.

Consulting stream

  • Formalize the business opportunity.
  • Design the main principles of the solution.
  • Quantify tangible benefits, investment and ROI.
  • Define the scope of the demonstrator (MVP).
  • Build the industrialization and transformation plan.

Data stream

  • Pre-frame the technical solution.
  • Qualify the data, infrastructure and governance.
  • Choose the algorithms: ML, LLM, Agents, Loops, causality.
  • Design and validate the POC, code the demonstrator.
  • Quantify industrialization and reduce technical risk.
Business plan โ†’ GO / NO GO decision

Six technical domains mastered

Data & governance

Quality, infrastructure, organization and governance of data.

Visualization

Management dashboards (e.g. cost-of-goods tracking).

Machine Learning

Forecasting, classification, segmentation (e.g. demand, profitability).

Large Language Models

Information extraction, generation, natural language processing.

Causality & Simulation

Causal graphs to understand and simulate scenarios.

Skills, Agents & Loops

Development of Skills, conversational agents, and process automation (Loops).