Expertise

What we actually do, and how deep it goes

Three ways in, one underlying capability: turning messy, high-value information into something a system can use, then wrapping it in a tool that fits an existing workflow.

Three ways in

Three ways we help

Add AI to your product or workflow

We design, build and integrate AI functionality into existing products, platforms, internal tools and customer experiences.

Search, recommendations, summarisation, document generation, classification, structured extraction, workflow automation, chat interfaces, user-facing features.

Typical shape

A development engagement through to a first integrated version. Ongoing support afterwards is optional: we can maintain it, or hand you the code, documentation and resources to run it yourselves.

Wrong for

Teams without a product or workflow to put it into yet. Start at line three.

Make your data AI-ready

AI is only as useful as the information underneath it. We clean, structure, connect and organise documents, reports, databases and knowledge sources so they can support reliable AI.

Document ingestion, structured extraction, foundational databases, data pipelines, metadata, vector search, APIs, monitoring, reporting reliability.

Typical shape

A scoped build on the archive or feed that matters. Pipeline support afterwards is optional: yours to keep and run if you would rather.

Wrong for

Anyone hoping to skip this step and go straight to a chat interface.

Get a practical AI roadmap

Not every AI idea is worth building. We start with a discovery workshop that digs into the root cause of what is actually going wrong, not just where to bolt AI onto an existing system, then assess feasibility and risk and define a practical roadmap.

That includes advice on data governance and the data-sharing agreements that constrain what you can actually do with your information, so the roadmap reflects what you are allowed to build, not just what is technically possible. The output is not a strategy deck for its own sake. It is a clear path to action, costed and sequenced.

Typical shape

A defined piece of work with one written output. No ongoing commitment attached.

Wrong for

Teams who already know what to build. Go straight to line one.

Capability

The layers underneath the three ways in

Data foundations

Document ingestion, structured extraction from PDFs and reports, table extraction, foundational database design, data pipelines, metadata, and the reliability of recurring data processes.

Document ingestion
Structured extraction
Table extraction
Database design
Data pipelines
Metadata and schema

Retrieval and search

RAG systems, vector search, semantic search over archives, query understanding, recommendation, and the evaluation needed to know whether any of it is actually working.

RAG systems
Vector search
Semantic search
Query understanding
Recommendations
Retrieval evaluation

Applied AI in products

Structured outputs, document generation, classification, summarisation, workflow copilots, and user-facing features integrated into products that already have users.

Structured outputs
Document generation
Classification
Summarisation
Workflow copilots
User-facing features

Delivery and operations

Cloud delivery across Azure, GCP and AWS, deployed into infrastructure you control, with monitoring, evaluation, documentation and production support once it is live.

Azure · GCP · AWS
Deployment
Monitoring
Evaluation
Documentation
Production support

How we choose

The positions we hold

Tool-agnostic and model-agnostic: Nothing is pinned to one vendor. Models change fast, and an architecture that assumes otherwise ages badly.
Data sovereignty by default: Systems run in infrastructure you control, in the region you choose. Your data is not used to train anything.
Modular architecture: Components you can replace one at a time, so a model or vendor change is a swap rather than a rebuild.
Short-term ROI first: We start with the workflow that matters and prove value at a scope small enough that finding out is cheap.

See what this looks like in production →

Let’s work out what is worth building.

Thirty minutes, no deck, no discovery phase. If it is not worth building, we will say so.

Start a conversation Email us directly