We tell you whether AI will work for your business, and what it will take. Before you spend anything.
We tell you whether AI will work for your business, and what it will take. Before you spend anything.
We work with businesses who believe AI could help them, and want an honest assessment of what that would involve.
Most organisations that invest in AI spend the money before they understand the problem. We establish the actual problem, whether AI is the right tool, and what it would take to succeed.
The organisations we work with have a genuine business problem and suspect their data could be doing more than it is. Typically, they are missing a clear picture of what is possible, what it would cost, and whether the conditions for success exist.
This includes business owners who have been approached by AI vendors and want an independent view; organisations that have invested in a system that did not deliver what was promised; founders who need a feasibility assessment before committing budget; and leadership teams that want to understand what their data could support before committing to a course of action.
A fixed-scope engagement over two to four weeks. We audit your data, assess what is feasible, recommend an approach, and produce a plan. Deliverables are written documents: a data audit report, a strategy document, and an architecture specification.
Most engagements start here.
Get in touch →Advisory engagement during the build phase, whether your team is delivering or an external supplier is. We review decisions as they are made and surface problems before they become expensive to reverse. Typically two to three days per week over eight to twelve weeks.
A monthly retainer for organisations post-launch. We review system performance, monitor for problems, track relevant developments in the field, and meet quarterly to assess whether the strategy remains sound. Two to four days of engagement per month.
Work has included: helping a legal services firm make its document archive searchable and queryable; building fraud detection for a fintech in a regulated production environment; developing a private AI system for a market research company that handles sensitive client data; AI-assisted diagnostics in medical imaging; intelligence extraction from unstructured records for organisations with data sovereignty requirements; and feasibility assessments for organisations at early data maturity.
Structured knowledge from client work, explorations, and deployment challenges.
Tools and products available for subscription.
Typed inference pipelines over privately hosted open-weight models. Define your task, build your pipeline, measure and improve.
Learn more →Behaviour observability for developer-founders. Structured JSON event logging with session-level aggregations, webhook triggers, and daily summaries -- no dashboards, no SDKs, no tracking pixels.
Visit Clientlog →
A multilingual children's story generator. Choose a language, a theme, and a cast of characters -- Popstory writes the story. Built with and for younger readers.
Visit Popstory →Declarative workflow execution engine. Define dependency graphs in YAML; runfox resolves and advances them.
PyPI →JSONLogic extended with JSONPath variable resolution. Compose conditional logic as data structures.
PyPI →A thin, typed wrapper over the AWS DynamoDB client. Dataclass-based item definitions with clean get, put, and query patterns.
PyPI →