AI Automation
Not hype, measurable wins. We install LLMs, RPA and data flows so they actually run in production.
Automation has become an 'AI will solve it' conversation. In practice, most workflows are solved by picking the right tool for the right step. Sometimes that is an LLM, sometimes a Postgres trigger, sometimes a well-written cron.
We map the existing process first, measure repetitive steps, mark the points worth automating. AI joins the system only when we can express the saving in minutes per person.
Example scenarios
Automated summarisation
Structured summaries for clinical notes, contracts, or support tickets.
Intelligent routing
Sending inbound requests to the right team, at the right priority.
Gated assistants
Two-step processes that keep humans in the loop while reducing the load.
Talk about this service
A two-sentence message is enough. We reply within the same business day — without the "innovative solutions" jargon.