From "where do we start?" to a working, production-ready proof in six weeks.
Start here if you're exploring AI and need a realistic, value-led plan — not a slide deck.
A tool your team uses to collect value cases across data, ML, and AI — then turns them into a roadmap leadership can act on.
Each value case is tagged to the datasets, skills, and tech it needs, so dependencies and readiness are visible from the start. Two views come out of it: a bottom-up roadmap your teams own, and an executive roadmap that shows leadership where the value is and what it takes to get there.
Build a shared understanding of AI across your leadership team — what's possible, what's hype, and what's relevant to your business.
A clear-eyed assessment of your AI readiness — data, technical capability, organisational maturity — with a prioritised roadmap and plan.
Rapid proof-of-value on your actual data. See AI working on your specific use case before committing to full implementation. Typically 1–2 weeks.
Map current manual processes and identify automation opportunities. Design AI-powered workflows that integrate with your existing systems.
A fast proof-of-concept for a single workflow — working automation in 2–3 weeks to validate ROI before a broader rollout.
Full-stack delivery — data, models, software, and the services to keep it all running.
Full-stack implementation: data pipelines, ML models, AI agents, user interfaces. Production-ready systems on Snowflake, Azure, or your preferred stack.
Full-stack product and platform engineering — the software around your AI and data, not just the models. Web apps, APIs, and platforms built to last.
We run it for you: monitoring, support, and continuous improvement so your data, AI, and software keep earning their place after launch.
Bespoke AI implementations for specific use cases. Fixed-scope projects with clear deliverables and timelines — ideal for well-defined problems.
AI systems for teams handling confidential data. Data separation, compliance guardrails, and audit trails built in from day one.
Production deployment of AI-powered workflows. Multi-step automation, system integrations, monitoring, and ongoing optimisation.
A workshop for teams adopting agentic coding — a hands-on track for engineers, and a capability briefing so CTOs and execs understand what it changes and where it pays off.
Hands-on leadership for teams building with AI — strategy and delivery, without a full-time hire.
Part-time ML/AI leadership (2–3 days/month): strategic guidance plus hands-on delivery. A fractional CTO for your data and AI initiatives.
Most teams start with Value Roadmapping or the Idea → Pilot Programme to find the value quickly — but we'll help you find the right entry point for your situation.