AI Consulting
Before any build, the decision: where AI pays in your operation, on which systems, under which rules. You leave with an architecture and a reason for each choice.
- AI Strategywhere AI pays in your operation, and in what order.
- Solution Architecturemodel, runtime, connectors; where the data may go and where it may not.
- Implementation Supportan engineer beside your team through the build.
- Expert Guidancea senior opinion when a decision needs one.
- Tutoring & Workshopshalf-day sessions for the people who decide.
Every engagement starts here, and two weeks later you have a go or no-go.
Generative AI
Assistants that answer from your documents, agents that run a process end to end, models tuned on your data, running in your assistant, on your hardware, or in the cloud on our terms.
- RAG Systemsassistants that answer from your documents, with the source cited.
- Agentic Workflowsagents that run a process end to end and hand over the exceptions.
- Fine-tuning Modelsmodels tuned on your data for your vocabulary.
- Local LLMopen models on your hardware when compliance requires it.
- Scalable & Optimizedthe same build at production load and cost.
The practice behind AI Skin and the Headless Agent Builder.
Machine Learning
Churn, demand, risk: models trained on your history and kept honest in production. When the data cannot move, federated learning trains across sites without pooling it.
- Churn Predictionwho is about to leave, and the next action for each.
- Forecastingdemand, cash, capacity: the number before it happens.
- Federated Learningtraining across sites without moving the data.
- Privacy-Preserving MLmodels that never see the raw record.
- Data Protectionwhat leaves, what stays, and the record of both.
Privacy by design, GDPR fluency, and a number to measure against.
AI Training
Two pathways. Developers learn to code with agents against your house standards. Business teams learn to work inside the assistant with the skills the skin ships.
The skin keeps growing after we leave.
Four stages, each with a price. Three of them end.
- 01 / 04
AI Discovery
- Two weeks
- fixed fee
The problem in one sentence, your data seen, one prioritised backlog and a go or no-go.
Learn more - 02 / 04
AI Pilot
- Weeks
- fixed scope
A working agent or skin on your data, with the failure cases written before anyone trusts it.
Learn more - 03 / 04
AI Rollout
- Staged
- one agreement
Production on your systems, under your permissions, with our team after.
Learn more - 04 / 04
AI Operations
- Monthly
- rolling
We keep the system running once it is live: monitoring, the fixes, an agreed scope of change each month, and a one-page report.
Learn more
Companies we have worked with
We bring three products of our own to an engagement.
Built by us, run by clients, sold with a service or alone. Each answers a specific need.
Which of these you need, and in what order.
AI Discovery. Two weeks, fixed fee, and it ends with your opportunities ranked by value and effort, the numbers behind the top three, and a roadmap. Nothing gets built until you have decided what is worth building.
Then skip Discovery and start at the pilot, which builds a working system in two to four weeks. We will still spend the first days on the design, because the part that breaks a build is usually the integration, not the model.
They are stages of the same path. Discovery decides what to build, the pilot builds one thing and proves it, Rollout takes it into production with the governance and the training around it, and Operations keeps it running. Each one ends, and you choose whether to take the next.
No. Expert Guidance is a senior engineer your team can ask, by the hour or by the month, with no package around it. Training runs on its own too, for developers and for business teams.
None of it has to. On-premise and private deployment are part of what we sell, and for machine learning across sites that cannot pool data, federated learning trains the model without moving the data.
Bring us the problem nobody has cracked yet.
We are a small team of senior specialists. We pick the right model and the right layer, and we build the least machinery that does the job. You get a call with an engineer, not a sales deck.