We design and build AI systems that help teams forecast, decide, and act with the data already inside their business.
Companies at scale have spent a decade collecting data, buying dashboards, and trialling AI tools. The leverage now sits one layer deeper.
Reports and BI tools answer questions you already knew to ask. The hard problems sit in the data you haven't connected yet.
Generic models trained on the internet are useful at the edges. They are not what you need at the core of how your company operates.
Real operating advantage now lives in systems built on your proprietary data, embedded into your workflows, owned by you.
We design and engineer three families of intelligence systems, each built around a client's data, decisions, and workflows.
For sales and marketing leaders who need a system that decides where attention goes, not another dashboard that describes it.
Built for a regional real estate group: an intelligence layer ranking accounts by buying-readiness, embedded into their CRM.
For organisations whose institutional knowledge sits in documents, calls, and the heads of senior staff. We make it operational.
Built for a professional services firm: an internal AI brain employees use to retrieve precedent, contracts, and project context in seconds.
For finance and operations leaders who need defensible projections, not gut calls dressed up in spreadsheets.
Available as part of broader engagements where forecasting underpins commercial or operational decisions.
A structured methodology refined across engagements. Multi-month, senior-led, and accountable for the system we build.
Joint diligence with leadership and data teams. We map decisions, data, and workflows, and produce a system architecture and engagement scope, not a deck.
Engineering, data modelling, model development, and integration into existing tools and infrastructure. Senior delivery from people who have done this before.
Productionisation, monitoring, governance, and handover protocols. No model goes live without measurable performance criteria and rollback plans.
Continuous iteration as your data, market, and business change. We measure, retrain, refactor, and extend the system through the engagement.
Engagements run over months, not weeks. They are led by the people doing the work, with senior accountability from day one.
Six principles that govern every engagement. They are why our clients work with us, and why some clients we politely turn away.
We build infrastructure that becomes part of how a business operates, not point solutions that gather dust.
We work inside our clients' operations, with their teams, on their problems. Engagements are long enough to matter.
No model goes live without measurable performance criteria. We design the evaluation harness before we write production code.
Models, code, data architecture, and documentation transfer to the client by default. We are not building a moat at your expense.
Engagements are led by the people who do the work. No bait-and-switch from sales pitch to junior delivery.
We measure systems by the commercial outcomes they produce, not by deliverables shipped or hours logged.
We're deliberate about who we take on. The engagement is intense and the work is real.
We unified CRM data, listings activity, and external market signals into a system that prioritises which agencies the sales team contacts each week. Built around their existing workflow, not on top of it.
Telemetry, route, load, and maintenance data unified into a predictive model that flags routes likely to incur excess fuel burn and vehicles trending toward breakdown before they fail. Classical data-science fundamentals, feature engineering, regression and survival modelling, monitored in production, not an LLM wrapper.
An intelligence layer scoring incoming loan applications against historical default behaviour, allowing the firm to qualify, price, and route applicants in real time. Built on classical credit-modelling techniques, gradient-boosted classifiers, calibration, drift monitoring, integrated directly into origination.
We designed a retrieval architecture across contracts, precedents, and project documentation, with an evaluation harness measuring answer quality before production rollout. Permissioning, governance, and audit by design.
Details available under mutual NDA. Engagement structure and methodology can be discussed in a discovery call.
We engineer bespoke intelligence systems against a single bar: measurable commercial outcomes. Not another process to manage, not another tool to maintain: infrastructure that compounds.
A short discovery conversation: the problem you're solving, the data you have, and whether an engagement makes sense for both sides.