Data and artificial intelligence

AI for your business processes

Document classification, assistants that know your information, intelligent search and prediction — AI where it adds value, not because it's trendy.

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Sound familiar?

Everyone says you need to do 'something with AI', but no one says what. Meanwhile your team keeps classifying documents by hand, hunting for information that already exists, and answering the same questions over and over.

Team hours spent reading, classifying and re-typing documents
Information that exists in your files but no one can find
AI pilots that never make it to production
Generic assistants that make up answers with total confidence

How we approach it

We start with the process that costs you the most time, measure before and after, and build on your data — with continuous evaluation, not faith. If AI doesn't add value in your case, we'll tell you.

Measurable use case

We identify together where AI actually saves time or reduces errors — and where it isn't worth the effort.

Honest evaluation

Before building, we assemble an evaluation set from your real cases. We know whether it works — we don't assume it.

Guardrailed implementation

The system cites its sources, admits when it doesn't know, and respects the limits we define with you.

Responsible operation

We monitor quality, cost and behavior in production. Improvements driven by real use.

What we deliver

Automatic classification of documents, requests or case files
Specialized assistants on your knowledge base with cited sources (RAG)
Semantic search across your documents and repositories
Structured data extraction from PDFs, forms and emails
Prediction models built on your operational history
Evaluation sets plus quality and cost monitoring in production

For your technical team

RAG pipelines with embeddings and vector search over your corpus, automated answer evaluation, versioned prompts and per-call observability. Commercial or open-source models depending on privacy and cost requirements.

RAG with embeddings, vector search and verifiable citationsAutomated model evaluation with custom test setsStructured extraction with schema validationPrompt versioning and per-answer traceabilityPer-use-case cost and latency control

Technologies we use

Python

PyTorch

scikit-learn

Spark MLlib

OpenAI

Claude

Gemini

LangChain

LangGraph

FAISS

OpenSearch

FastAPI

AWS

Google Cloud

Python

PyTorch

scikit-learn

Spark MLlib

OpenAI

Claude

Gemini

LangChain

LangGraph

FAISS

OpenSearch

FastAPI

AWS

Google Cloud

Where we apply this service

Health

Systems for hospitals, ministries and healthcare networks: clinical records, epidemiological surveillance, program management, territorial KPIs.

Environment and sustainability

Systems for environmental monitoring, forestry management, enforcement and impact reporting. Reliable data for both policy and operations.

Knowledge management

Platforms that organize institutional memory, document repositories and specialized search — including AI assistants grounded in your own corpus.

Higher education

Academic systems, learning platforms at scale, and portals for universities. Not corporate training: academic institutions with thousands of students.

Private enterprise

For corporations and mid-market companies that need solid internal systems: automation, supplier integrations, executive dashboards, field apps.

AI with a purpose, not pilots that die?

Tell us which process takes most of your team's time. We'll tell you quickly whether AI helps there — and if it doesn't, we'll say so too.

Let's talk