Your data and AI projects, delivered to production.
We scope the use case, build the data, train the models, design the agents and run the whole thing once live. One team, no hand-off.
We build, deploy and maintain AI solutions for our clients.
We always begin the same way, sitting down with your teams to understand the business before anything else. After that you can join us at any step, or hand us the whole chain.
Diagnostic
One day with your teams, then a map of what AI can do for you.
- A one-day workshop: practices, needs, available data
- A written summary: candidate projects, complexity, long-term benefit
- A steering team on your side for what follows
Project execution
Data first, then the product, module by module.
- Data collection, internal or external, and a dedicated warehouse
- Successive modules, each validated with your steering team
- An unpromising direction is changed, not pushed through
Delivery and training
In production, on our infrastructure or yours.
- Deployed on our infrastructure, operated by us, or on yours
- Presented jointly to the wider team: how it works, what for
- Training sessions whenever the project calls for them
Ongoing maintenance
We stay: the system is kept running, and kept current.
- Long-term support for the systems in production
- New models and advances in AI folded in as they arrive
- Monitoring, retraining and upgrades as usage grows
What we do
Data pipelines and platforms
We turn what you already have into a reliable, governed source for AI, on a platform you can run yourself.
Custom AI models
Classification, extraction, prediction and retrieval. We select, fine-tune and evaluate what fits the task, small models included, and deploy them on your data.
AI agents
Systems that read your data, decide, act and report back, with every run traced and a supervision your teams can audit.
Integration and operation
Delivered inside the applications your teams already use, then monitored, tuned and scaled once live.
Working with your teams
We work alongside your teams on what has to change around the system: the process, the ownership and the decisions it feeds.
Training
Sessions for the people who will use and run what we build, from the business teams to the engineers who inherit it.
In practice
Some of the systems we have built and run, across the sectors we work in, and the models we calibrate, fine-tune and keep current behind them.
- Healthcare
Research intelligence
Open-source models, on premise, read the global medical literature and clinical trials, connected to the CRM, and write the reports: complex publications turned into usable medical intelligence.
- Corporate intelligence
Enterprise knowledge agent
One conversational interface over the CRM and the documents on SharePoint, so a question gets its answer wherever the information lives.
- Training
Immersive role-play
Voice and video avatars play unscripted client meetings for wealth managers and clinicians, with real-time feedback and targeted micro-learning after each session.
- Finance
Investor relations and reporting
Semi-automated Q&A, summaries across multi-fund reports, consensus and divergence across assets, and faster due diligence, from the CRM and the files the teams already keep.
- Maritime
Fleet decarbonisation
Predictive models for optimal sailing speed and emission phases, predictive maintenance, and a data-driven way to qualify green technologies across the fleet.
- Machine learning
Custom models, calibrated
Gradient boosting, random forests, SVMs or deep networks (CNN, LSTM, TCN) estimated on your tabular data, time series and images, calibrated against real outcomes, and recalibrated when the data drifts.
- Fine-tuning
Open-weight models, tuned to your data
Open-weight LLMs and embedding models fine-tuned on your documents and your vocabulary, evaluated on a test set built from real cases, and served privately on our API or your infrastructure.
- Data
Labeling and synthetic data
Large-scale labeling of texts, images and videos, and synthetic data generated with GANs where real examples are rare or sensitive, so a model can be trained and tested all the same.
- Risk and compliance
Live supplier monitoring
Named-entity recognition models read the news, filings and documents as they arrive, tie each mention to the right supplier, and raise what matters: a sanction, a change of ownership, a plant shut down. Live, on unstructured data.
Your data stays yours
Sovereignty isn’t a feature we add at the end. It shapes the architecture from the first day: where the models run, who can reach the data, and what can be proven afterwards.
Deployed in your environment
Models and compute run inside your infrastructure, or on a sovereign cloud of your choosing.
You own what we build
Models, pipelines and code belong to you, in open formats, with no provider lock-in.
Security
Access stays limited to the people on your project, and your data never trains anyone else’s model.
Traceability
Where each piece of data came from, what transformed it, and which model used it.
Let’s talk about your project
Tell us what you are trying to solve. We will tell you what it takes, what it does not take, and where AI is genuinely the right answer.