Skillsize AI Services: Decision Engines and Operational Deployment

Make your expertise work across your business.

Skillsize helps businesses build and deploy AI decision engines, intelligent workflows and digital Specialists around their own expertise, data and operational requirements.

We work directly with your subject matter experts and delivery teams to capture how important work is performed, then build capabilities that apply those methods consistently.

Decision engines

Turn business criteria, evidence and expert judgement into structured tools that assess options, score performance, identify risks and recommend actions. Potential applications include investment prioritisation, supplier assessment, workforce planning, commercial diagnostics and resource allocation.

Operational deployment

Embed AI into everyday work: reviewing documents, analysing data, triaging requests, generating recommendations and routing outputs for approval or action. Connect individual tasks into repeatable workflows, with clear escalation points and human accountability.

Expertise capture and solution development

Codify specialist knowledge into reusable AI Skills. Combine these Skills into digital Specialists or tailored solutions for employees and customers, helping your organisation preserve knowledge and scale expert delivery.

Our delivery approach

We start with a focused business challenge and agree the intended outcomes. We then map the process and available data, design and build the capability, validate it with your experts, and deploy it into the working environment.

Integration can use APIs and MCP where appropriate. Human review, data protection and traceability are designed around the requirements of each use case.

The resulting capabilities can be maintained, refined and extended as your needs evolve.

We are looking to work with businesses that have a specific decision or operational process to improve, and with consortium partners seeking a practical AI delivery partner. A focused pilot provides a starting point to evaluate time saved, output consistency and usefulness before wider deployment.