Most businesses have more AI potential than they realise - buried in repetitive workflows, disconnected tools, and knowledge locked in documents. We identify the highest-value opportunities, prototype fast and build production systems with evals, monitoring and guardrails. Practical AI that ships, not slide decks about AI.
Custom agents built on Claude, OpenAI or open-source models - with tool use, multi-step reasoning and human-in-the-loop checkpoints. Deployed as APIs, Slack bots, internal tools or customer-facing features, depending on where the value is.
Retrieval-augmented generation systems that connect your LLM to your actual data - docs, databases, CRMs, wikis. Built with proper chunking strategies, embedding models and hybrid search so answers are accurate, not hallucinated.
API integrations, webhook pipelines and n8n/Make flows that eliminate manual handoffs. We identify the tasks your team does repeatedly that don't require human judgement, then automate them properly with error handling and audit logs.
A structured discovery sprint across your workflows, data assets and current tooling. We map where time is lost, where decisions are routine and where knowledge is siloed. Output: a ranked opportunity register with effort-vs-impact scoring and a recommended starting point.
System design for the chosen use case - prompt architecture, tool definitions, data pipeline design and integration map. We define success metrics and failure modes before building. A lightweight technical spec is reviewed and approved before development starts.
Two-week sprints. A working prototype by end of week two - something your team can use and give feedback on. Production build follows with proper error handling, retry logic, rate limit management and a test suite (evals) that catches regressions.
Production deployment with a monitoring dashboard tracking task success rate, latency, error rates and cost. We run a team enablement session so your people understand how to work with the system, what it can and can't do, and how to flag edge cases.
Tell us your most time-consuming repeated task. We'll come back with a realistic assessment of what AI can do about it.