Enterprise AI, one case at a time.
An AI project rarely succeeds because the model is good. It succeeds because the problem is well framed, the data is reachable and someone can tell whether the answer is right. These are the six requests we receive most often, and how we handle them.
An AI assistant that answers from your internal documents
Procedures, contracts, technical documentation: an assistant that searches your sources and cites what it relies on.
Read the use case →An AI voice agent for your inbound calls
Pick up every call, qualify the request, book an appointment or transfer: what a voice agent does well, and what it should not be allowed to do.
Read the use case →Automate document processing with AI
Invoices, contracts, purchase orders, case files: extract the data, check it and send it to your tools, with a human where one is needed.
Read the use case →Add AI to your CRM or ERP
Account summaries, assisted entry, prioritisation, natural-language search: put AI where your teams already work.
Read the use case →AI audit: know where AI will help you, and where it will not
A review of usage, data and risks, and a roadmap that also says which projects not to launch.
Read the use case →Get your engineering team working with AI coding agents
Move from autocomplete to agents that ship whole tasks, without sacrificing code quality or security.
Read the use case →Is your situation close to this one?
Describe it in a few lines. We will tell you whether AI is the right answer — and we will also tell you when it is not.
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