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AI Build

Purposefully-built AI

We build new AI in-house — for clients, and as our own ventures. Domain AI on your knowledge, AI products that drive revenue or savings, and self-directed R&D where we choose the domain and own the IP.

Domain AI

Your knowledge, made to answer

A domain vector-database paired with an assistant, built on your content — medical, legal, any specialist field. The first question is architecture: should it live on-premises, in the cloud, or at the edge? We settle it with a cost-benefit analysis — short- and long-term cost, security, and IP — before you build. We have built one for surgical robotics; the architecture travels, the knowledge is yours.

Domain assistant

Surgical-robotics assistant

For Symani microsurgery robotics, we prototyped a domain assistant — a vector-database chatbot and a deep-research agent — over specialist surgical knowledge.

Architecture consultancy

On-prem vs. cloud vs. edge

Where your domain AI lives is an architecture decision with lasting consequences. We run the cost-benefit analysis — short- and long-term cost, security, and IP — so you deploy in the right place, for the right reasons.

In-house R&D

Practice makes perfect

We don't only build to a client's spec. We pick the domain or the market ourselves and develop our own AI — domain vector databases, retrieval chatbots, deep-research agents, and other agents — and we own the IP. When one path runs short on data, we follow it to an adjacent application that has what it needs.

Self-directed builds

Our own models & products

We choose a domain or a market with potential, then build it — domain vector databases, retrieval chatbots, deep-research and task agents — as products we own.

We follow the data

A constraint becomes a new line

When data limits one application, we pivot to an adjacent one that's viable — turning a dead end into a new product, and new IP.

The IP is ours

Original, documented, owned

The models and products we develop are protected — trademark, copyright, and documented provenance. Original IP, not borrowed.

How a build works

A mindful, systematic pipeline

No demos that die in a drawer. Every build runs the same disciplined path — from the opportunity to a measured result.

01 · Scope

Find the real opportunity

Where AI earns its keep in your business — a new revenue stream, or a cost and bottleneck worth removing. And the candour to say where it doesn't.

02 · Architect

Decide where it lives

On-prem, cloud, or edge — settled by a cost-benefit analysis across cost, security, and IP before a line of code is written.

03 · Build

Build it in-house

Domain vector databases, RAG, agents, and real-time pipelines — built on your knowledge, on your infrastructure, owned by you.

04 · Measure

Prove the result

Impact tracked to the bottom line. To a researcher, measurement is a given, not a feature.

AI ROI

Turn AI into revenue and savings

We develop AI products that generate new revenue streams and/or solve long-standing internal problems — and we measure the impact to the bottom line. Built for you, or launched as our own venture.

Revenue

New revenue streams

AI products that open a revenue stream you didn't have before.

Savings

Cost & bottleneck removal

AI that removes a cost or a bottleneck inside the business.

Measured

Impact to the bottom line

Tracked and proven to the bottom line — not a demo.

Recent example · new revenue stream

Crime-mapping to sales pipeline

For a security firm, we paired open crime data with AI to surface prospect businesses most likely to need protection — turning public data into a lead engine the sales team didn't have before.

Engage

Ready to build your own domain AI?

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