We help organisations implement GenAI in practical, controlled ways. From document intelligence to assistants and workflow automation, our focus is on usefulness, reliability, and responsible integration into existing systems.
Start small. Most of our engagements begin with one workflow or document type. We scope for a focused MVP that proves value before scaling. This reduces risk, shortens timeline, and lets you learn what works in your environment before committing to broader rollout.
LLM API costs, which depend on usage volume and model choice. Hosting infrastructure if deploying in your environment. Potential maintenance and iteration as your use case evolves. We provide cost estimates and usage projections during scoping so there are no surprises after launch.
They deliver the most value when applied to specific, repeatable tasks that already consume significant time such as document processing, knowledge access, drafting and summarisation, decision support, and workflow assistance. Broad or unspecific use cases tend to underperform. The value comes from reducing manual effort, improving consistency, and helping teams move faster on work they already do.
GenAI systems are designed with boundaries. We manage risk by scoping AI to specific tasks, designing human review into workflows, and ensuring outputs are easy to check, correct, and trace. AI is treated as a support layer, not a decision-maker. Guardrails, escalation paths, and monitoring are built into the solution so teams stay in control of how AI is used.
We get where you’re coming from. Some problems are better solved with rules, automation, or better process design. GenAI makes sense when you're dealing with unstructured information, variable inputs, or tasks that need interpretation rather than exact logic. If a simpler solution exists, we'll let you know. The goal is solving your problem, not using AI for its own sake.
