Built by WCAI

An AI decision becomes concrete when a team has to connect it to a real process. Who can authorise a payment? Which records may a model access? What happens when the answer is wrong or the supplier is unavailable? WCAI's building practice centres on those operating questions.

We work alongside the people responsible for the workflow, connecting strategy and governance to implementation. The scope can be a bounded prototype, an evaluation, a reference architecture or support for a production service. Agreeing that scope matters: evidence from a prototype supports a different commitment from evidence about a live service.

Start with the work and its boundary

A useful build begins with a defined task, its current performance and the constraints that an operator must respect. For a finance workflow, that might mean the types of reconciliation exceptions staff handle, the systems of record and the authority needed to change a transaction. For a knowledge assistant, it includes the documents it may retrieve, the questions it should decline and how a reader checks its answer.

The first design decision is often how much authority to grant. Reading a record, proposing a change and executing a change require different controls. We connect those permissions to named owners, acceptance evidence and a recovery procedure before treating a technical demonstration as an operating capability.

Test the service people will actually run

Evaluation should include difficult cases, retained human work, integration failures and recovery. A model's accuracy is one part of that evidence. Staff must also be able to detect a failure, understand the available response and restore the process within an agreed boundary.

The financial case needs the same discipline. Time released can create useful capacity without reducing cash expenditure. Supplier costs, review effort and transition work belong in the decision alongside the expected benefit. Our working resources provide methods for documenting those assumptions and testing an operating boundary.

How to assess implementation evidence

A credible project account identifies the problem, WCAI's specific contribution, the deployment status and the evidence behind its outcomes. An experiment can establish a useful limitation. A prototype can demonstrate a feasible approach. A live implementation needs evidence about operation, ownership and support. Quantitative results require their measurement period and method; qualitative lessons need enough context to judge their relevance.

No project accounts are listed here yet. We will add them when the contribution, evidence and permission to disclose are established. Individual experience at previous organisations remains career experience rather than a WCAI project.

If you have a workflow ready for investigation, describe the decision you need to make, the current process and the constraints on implementation. Discuss a related initiative or read about our advisory approach.