Engine B · CLA · 2025
An AI-first substantive testing platform for a global consultancy
I led the design of an AI-first substantive testing platform inside a global consulting firm, standardising how audits are executed across teams and geographies. Working as the first product designer, I established the product design practice, partnered closely with engineering and audit SMEs, and designed a scalable agent ecosystem that preserved human judgment while improving consistency and audit quality. The platform reduced fragmented workflows to a single global standard and saved an estimated 30 to 40 thousand auditor hours.
The key decision
Deep integration with CLA's core PFX system was compelling: seamless data flow, role-aware experiences across associates, managers, and partners. But CLA's data architecture had grown organically across many external vendors and stacks; the surrounding infrastructure was too fragmented to merge safely within our constraints.
We chose momentum with integrity: a robust, auditable agent ecosystem with limited manual round-tripping, built so deeper integration could layer in once the broader data architecture matured.
The system
How it worked
Auditor selects a client & engagement
Agent generates a truly random, methodology-approved sample
Missing artefacts extracted & fed back automatically
Auditor reviews, confirms, and finalises the test
Validation & rollout
Visuals
Playground
Try the AR substantive testing flow. Select accounts, run an inquiry, and review analytics.
- Role
- Lead Product Designer
- Year
- 2025
- Focus
- AI · SaaS · Enterprise