Service
AI automation for business
AI agents and workflows that absorb repetitive work: documents, lead qualification, support and reporting, with the final call left to people.
AI automation pays off where a task repeats often, has a verifiable result and consumes expensive human time. Not every process deserves a model, and the first thing we do is tell you which ones do not.
What we automate in practice
Document processing: supplier invoices, contracts, certificates, scanned applications.
Inbound triage: classification, qualification scoring, routing to the right person.
Customer support: a draft reply grounded in history and documentation, reviewed by a human.
Research and summarisation: tender monitoring, competitor tracking, regulatory updates.
Reporting: weekly summaries generated from the real data in your systems.
How we build it
Measure the baseline: cases per month, time per case, the error rate you can accept.
Define the success criterion before writing code; if it cannot be measured, we do not automate it.
Build the flow with a human in the loop and a confidence threshold; below it, the case goes to a person.
Run in parallel with the manual process until the numbers confirm the result.
Hand over with monitoring, a monthly cost figure and an escalation plan.
Technologies
We use models from Anthropic and OpenAI, and open-source models running locally when data cannot leave the client's infrastructure. We build RAG over internal documentation, orchestrate with Python or Node.js, and connect existing systems through APIs, n8n or message queues.
Privacy and compliance
For European Union clients we configure processing in EU regions, with a documented GDPR legal basis and no training of models on client data. For sensitive workloads we can run models inside your own infrastructure.
What we will not do
We do not let a model send commercial offers on its own, set prices, or answer on the company's behalf without review. Automation reduces work, not accountability.
What the service includes
- Data extraction from invoices, contracts and PDFs
- Automatic qualification and routing of inbound requests
- Internal assistants grounded in your documentation (RAG)
- Support replies proposed for review, not sent blind
- Scheduled summaries and generated reports
- A full log of what the model decided and on what basis
Frequently asked questions
Does our data reach the model provider?
It depends on the configuration, and you decide. We use business accounts where providers do not train models on client content, we can restrict processing to European Union regions, and for sensitive data we can run models inside your own infrastructure.
What happens when the model gets it wrong?
Every result carries a confidence score. Below the threshold agreed with you, the case is routed to human review automatically. All decisions are logged, so it is possible to reconstruct afterwards what the model proposed and what a person corrected.