Industries Six sectors Named constraints, not verticalised copy

AI solutions by industry.

A generic AI system fails in a regulated enterprise for reasons that are specific rather than general: a named regulation, a data shape nobody documented, a failure mode the business already knows about. Each section below starts from those.

WHY THE VERTICAL MATTERS

Most of what an AI system needs is the same everywhere: retrieval that finds the right passage, evaluation that catches regression, an interface that fails visibly rather than silently. We do not think the underlying engineering is meaningfully different by sector, and a consultancy claiming otherwise is usually selling the same architecture six times with the nouns swapped.

What genuinely differs is the constraint set. In lending, a decision has to be explainable to a customer who was declined. In healthcare, a note has a clinician's name on it and therefore their accountability. In legal, an uncited proposition is worse than no answer at all. In manufacturing, an alert nobody acts on is the same as no alert. Those constraints change the design of the system, not the label on the marketing page — and that is what these sections are about.

Each industry index below opens onto specific use cases. That structure is deliberate: a page that tries to cover a whole sector says nothing precise about any part of it.

ALL INDUSTRIES

IND.01 Financial Services AI in banking, lending and insurance where decisions must be explainable and auditable. 3 PAGES IND.02 Healthcare & Pharma AI over clinical and administrative data, built for privacy and traceability. 3 PAGES IND.03 Legal & Compliance AI for contract review, research and discovery, with citation as a hard requirement. 3 PAGES IND.04 E-Commerce & Retail AI for merchandising, support and demand forecasting in retail. 3 PAGES IND.05 SaaS & Technology AI features inside a software product, and AI inside the team that runs it. 3 PAGES IND.06 Manufacturing AI for production, quality and supply chain in industrial settings. 3 PAGES IND.07 Insurance Claims triage, underwriting support and fraud detection, designed for a regulated decision that a person still signs. → IND.08 Public Sector AI for public bodies: procurement reality, data sovereignty, transparency duties and the records an audit will ask for. → IND.09 Logistics & Freight Document pipelines, exception handling and planning support for freight, ports and supply chains. →

WHAT IS THE SAME EVERYWHERE

Traceability

Every output attributable to a source and a model version. In a regulated sector this is the difference between a system that survives an audit and one that gets switched off after the first question about it.

A visible failure mode

Systems that escalate when uncertain rather than answering confidently. Retrieval does not eliminate model error; it makes it detectable and attributable, which is the true claim and the more useful one.

Evaluation that keeps running

A regression gate built from real examples of your task, running after launch rather than only before it. Without it, quality decays invisibly and nobody can say when it started.

DESIGN TARGETS

INDUSTRY VERTICALS

100%

CODE DELIVERED TO YOUR REPOS

2–6 wk

TIME TO FIRST PILOT

PLATFORM LOCK-IN

Properties we design and build to, not measured client outcomes.

QUESTIONS

QUESTIONS — 3

No. These six are where we have written the constraints down, not the boundary of what we build. The first conversation in an unlisted sector is the same one: what decision does this system influence, who is accountable for it, and what does the regulator or the customer need to be able to see.

No, and we would be sceptical of anyone claiming to. What is sector-specific is the retrieval corpus, the evaluation set, the escalation policy and the audit trail. The model underneath is chosen per workload from the same families we would use anywhere.

More than the model choice and less than people fear. It mostly determines what has to be recorded, what has to be explainable, and where a human has to remain accountable — all of which are architectural decisions best made in week one rather than discovered during a security review.

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Reference

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