From choosing the right use case to deploying the solution, we work with your team to build AI assistants, agents, and workflows that connect to your systems and support real operations.
Across industries. Built around your people, data, and processes.
What we can help with
Bring an idea, a prototype, or a workflow that needs improving. We can help at any stage.
Work out where AI can make a useful difference. We assess workflows, data readiness, platform options, integration needs, and how to measure success.
Build and deploy AI that operates inside your business: assistants that use your knowledge, agents that call your systems, and workflows that help teams complete tasks.
We work alongside your team in a forward deployed engineering model: learning the business process, building against real systems, and improving the solution with users.
What we can build
These are examples of solutions we can scope around your systems and requirements.
Help staff find answers in policies, procedures, and internal knowledge, with source references and access aligned to their permissions.
Look up records, prepare updates, and carry out approved actions through your APIs. Use existing business rules and human review for consequential steps.
Extract information, classify requests, draft responses, and route exceptions to a person. Connect each step to the team and system responsible for the next action.
Add search, summarisation, recommendations, or an assistant to an existing application, with an interface and evaluation process suited to its users.
Built for production
Runtime AI is the solution operating in your business: handling requests, using tools, and responding to real data. We design how it behaves, how you measure it, and what happens when something goes wrong.
We agree operational requirements early, then build the controls and visibility your team needs to run it.
Ways to work together
Choose an engagement around the decision you need to make or the solution you need to deliver. Scope, deliverables, and acceptance criteria are agreed before work starts.
For teams deciding what to build. Map the workflow, assess feasibility, identify dependencies, and define a pilot with measurable outcomes.
For a defined use case or an existing prototype. Build the application and integrations, evaluate it with users, and deploy against agreed release criteria.
For ongoing delivery alongside your team. Work through a shared backlog, release in increments, and build the capability to maintain and extend the solution.
Questions before you start
No. Our AI consulting and implementation services are available across industries. Education is a specialism, with SIS and SITS expertise for organisations that need it.
We start with your current applications, APIs, identity setup, and cloud environment. Where useful, we can build retrieval-augmented generation (RAG) for knowledge access or Model Context Protocol (MCP) integrations for AI tools. Platform choices follow your requirements.
We agree hosting, model provider, data flows, access, retention, and logging requirements during discovery. Deployment in your cloud can be considered where supported; third-party model processing is assessed separately so the boundaries are clear.
Handover includes the agreed code, configuration, evaluation tests, and runbooks. We can scope ongoing support and improvements, or help your team take over day-to-day operation.
Tell us what your team does today, what you want to improve, and which systems are involved. We will help you shape the next step.
