AI assistants and copilots that work inside your business
Copilots, RAG assistants that answer from your documents, and computer vision, built on models such as Claude and GPT and connected to your data, with permissions, evaluation and cost tracking.
Where AI usually pays off first
Repetitive work piles up
Invoices, order changes and emails wait days for someone to check and re-key them
Answers are buried in documents
Staff search shared drives for the latest policy or contract term, and still get it wrong
Pilots stall before production
Demos work on sample data, then stop when they meet real systems, permissions and owners
AI with controls built in
Every workflow ships with a way to measure it and a person who owns it.
| Measure | Target | Result |
|---|---|---|
| Answer accuracy | ≥ 95% | 96% |
| Sent to human review | ≤ 10% | 8% |
| Cost per run | ≤ $0.05 | $0.04 |
- Use-case shortlistWorkflows ranked by volume, value, data access and risk
- Working workflowAgents, copilots or RAG assistants connected to your systems
- GuardrailsPermissions, grounding in your sources, and human approval where it matters
- EvaluationTest sets and accuracy tracking before and after launch
- Cost monitoringSpend per run and per workflow, visible to the owner
- Computer visionImage and video models where the workflow needs them
Take repeatable manual work off your team
Invoice checks, order changes, email triage and document lookups eat hours every week. We automate the routine steps with AI and route the exceptions to the right person.
Today
- Manual checks and re-keying
- Queues that grow at month-end
- Answers depend on who you ask
- Pilots stuck in demo mode
After
- AI handles routine steps, people review exceptions
- Volume handled without extra headcount
- Answers grounded in your own documents
- Measured accuracy, cost and ownership
Results you can check
We agree a baseline before work starts, so the result is measured, not claimed
Start with one workflow, prove it, then scale
Discover
Map the workflow, its volume and its cost today
Design
Choose agent, copilot or RAG, and where people stay in the loop
Build
Connect to your data and systems
Evaluate
Test against real cases before launch
Roll out
Launch, monitor and expand to the next workflow
We build on the stack you already run
- Claude
- OpenAI GPT
- LangChain
- Vector databases
- Python
- OpenCV
Explore the rest of our AI work
See it in practice
From manual lead handling to automated marketing operations
Marketing and CRM data consolidated across more than twenty EMEA countries, with lead management automated end to end
What buyers ask before starting
Which AI model do you use?
The one that fits the task, cost and data rules.
Will AI see data it shouldn't?
No. It follows your existing permissions.
How do you stop wrong answers?
Answers show their sources, and low-confidence cases go to a person.