Services

AI development services

We build custom AI applications, automate business workflows and integrate AI into existing software—with specialist experience in healthcare.

Choose a service

Each page covers who the service is for, use cases, scope, requirements, delivery and ownership.

Specialist sector

Healthcare AI development

Healthcare AI development: clinical document processing, patient-facing assistants and health-data workflows, built with your clinical and compliance teams.

View Healthcare AI

AI agent development and workflow automation

AI agents and workflow automation that handle multi-step business processes across email, CRMs, ERPs and internal tools, with human review where it matters.

View AI agents & automation

AI integration services for existing software

Add AI features to your existing software or SaaS product, such as search, summaries, classification and assistants, without replacing your systems.

View AI integration

Document intelligence and RAG

Document intelligence and retrieval-augmented generation (RAG): search, question-answering and data extraction over your documents, with cited sources.

View Document intelligence & RAG

Custom AI application development

Custom AI application development: new web and mobile applications designed around an AI capability, from prototype to production.

View Custom AI applications

AI chatbot development

AI chatbot development for customer-facing websites, apps and support channels: chatbots that answer from your approved content and hand over to your team when needed.

View AI chatbot development

Custom model training and fine-tuning

When a general-purpose model isn’t accurate enough for your domain, we train or fine-tune models on your data. We recommend this only after testing simpler options, because it adds data-preparation and maintenance work.

When it fits

  • Specialised terminology or formats general models handle poorly
  • Requirements to run a smaller model in your own environment
  • High volumes where a tuned smaller model reduces running costs
  • Consistent output style or structure that prompting can’t achieve

What’s involved

  • Assessment of whether fine-tuning is needed at all
  • Training-data preparation and labelling guidance
  • Training and evaluation against a baseline model
  • Deployment, monitoring and a retraining plan
  • Model-weight ownership and licensing agreed in the statement of work

Our team has trained AI models in-house for our own platform, BioHarmony.

AI consulting

Short, focused engagements to help you decide what to build, how, and whether AI is the right tool.

Typical questions

  • Which of our processes would benefit most from AI?
  • Should we build, buy or extend an existing tool?
  • Is our data ready, and what would it take?
  • Can you review an AI system or vendor proposal?

Deliverables

  • Use-case assessment and prioritised shortlist
  • Recommended architecture and model options
  • Effort, cost and risk estimates
  • A delivery plan you can run with us or another team

Agency partnerships

Agencies and software consultancies bring us in to deliver the AI part of their client projects, while they keep the client relationship.

How it works

  • Scoping support during your sales process
  • Delivery of AI features alongside your team
  • White-label or co-branded arrangements by agreement
  • Documentation your team can support afterwards

What we need

  • A clear point of contact on your side
  • Access to the client brief, systems and data
  • Agreed responsibilities for client communication
  • Agreed commercial terms before work starts

Ways to work with us

Discovery & prototype

A short, fixed-scope phase to test feasibility on your data before committing to a full build.

Fixed-scope project

A defined deliverable, timeline and price, agreed in a statement of work.

Ongoing team

Time-and-materials engagement for evolving products, with regular planning and demos.

How a project runs

  1. Discovery

    Understand the workflow, the data and what success looks like. Agree scope and measurable targets.

  2. Prototype & evaluate

    Test the approach on a sample of your data against agreed criteria before a full build.

  3. Build & integrate

    Develop, connect to your systems and test with your team, with regular demos.

  4. Deploy & support

    Release to your chosen environment, hand over documentation and agree ongoing support.

Not sure which service fits?

Describe the problem and we’ll suggest an approach. If AI isn’t the right tool, we’ll say so.