AI Solution Design
Translating a business problem into a workable AI approach, with clear inputs, outputs and success measures.
- Problem framing and requirements
- Approach and architecture options
- Evaluation criteria
Intelligent Systems
AI Built Around Your Data and Workflows.
When off-the-shelf tools do not fit, we help design and develop AI features and applications that work with your systems, your data and the way your teams operate.
Where It Helps
Common Situations We Help With.
Custom development makes sense when the problem is specific to your business and generic tools only get you part of the way.
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A process depends on judgement calls that could be supported by AI
We turn the decision into a defined AI task with clear inputs, outputs and a way to measure success.
AI Solution Design -
Packaged AI tools do not fit your data or workflow
We select and adapt models to your own data and constraints rather than forcing a generic tool to fit.
Model Development & Tuning -
You want to add AI features to an existing product or internal tool
We connect AI capabilities to your application through well-defined services, with fallbacks and human review.
AI Integration -
An idea needs a pilot before a larger commitment
We build a small working version with real data so you can judge the idea on evidence.
Prototypes & Pilots
Capabilities
What We Can Help You Deliver.
We can take on a single piece, such as a prototype, or carry an idea from design through to integration.
Model Development & Tuning
Selecting, adapting or training models that suit the task, the data available and your constraints.
- Model selection and comparison
- Fine-tuning where appropriate
- Testing against agreed criteria
AI Integration
Embedding AI capabilities into the applications and workflows your teams already use.
- API and service integration
- User experience for AI features
- Fallbacks and human review
Prototypes & Pilots
Small, well-scoped builds that test whether an idea works before larger investment.
- Proof-of-concept builds
- Pilot with real users
- Findings and next-step recommendations
How We Work
How an Engagement Comes Together.
We test ideas early with real data, so decisions about larger investment rest on evidence.
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Phase 01
Frame the Problem
We define the task, its inputs and outputs, and how success will be measured.
OutcomeAgreed requirements and evaluation criteria
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Phase 02
Prototype
We build a small working version using a sample of your data.
OutcomeEvidence of what works and what does not
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Phase 03
Develop & Integrate
We harden the solution and connect it to your applications and workflows.
OutcomeA tested feature running inside your systems
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Phase 04
Evaluate & Hand Over
We check results against the agreed criteria and document how to run and update the solution.
OutcomeDocumentation, findings and options for ongoing support
Related Services
Often Combined With.
How do we know whether we need custom AI or an off-the-shelf tool?
We start by checking whether existing tools can meet the need. Custom development is recommended only when your data, workflow or requirements make a packaged option a poor fit.
What data do we need to provide?
It depends on the task. During problem framing we identify the data required, review a sample with you and agree how it will be accessed and protected.
Who owns what is built?
Ownership of code, models and documentation is set out in the agreement for each engagement, and we discuss it with you before work begins.
Intelligent Systems
Have an AI Idea That Needs Building?
Describe the problem and the data you have, and we can talk through whether a custom approach is the right fit.