Automation that stalled
Suites nobody trusts, coverage plateaued, maintenance eating the sprint.
We benchmark the engineering skills your teams actually have, then close the gap with role-based programs, real project work and measurable capability — not seat licences nobody uses.
Suites nobody trusts, coverage plateaued, maintenance eating the sprint.
Legacy Selenium estates and no internal capability to modernise them.
Teams asked to "use AI" with no evaluation discipline or quality bar.
No objective read on who can engineer and who can only execute.
Process, tooling, automation and AI readiness scored against a reference model.
Individual and team-level skill scores, mapped to the roles you're hiring for.
Framework review, migration strategy and hands-on enablement of your engineers.
Migration path off legacy suites, with a framework your team owns afterwards.
AI-assisted testing, LLM evaluation and agentic testing brought into your SDLC.
Quality bars, evaluation harnesses and governance for AI features you ship.
A standing curriculum for your QE org, with cohorts, labs and assessments.
Tester, automation engineer, SDET and architect tracks run against your stack.
Time-boxed builds that surface capability and momentum inside your teams.
Maturity assessment and skill benchmarking across the org.
Role-based tracks and success metrics agreed with your leadership.
Cohorts run against your codebase, tooling and domain.
Project work and hackathons that land capability in production.
Re-benchmark and report the delta against the baseline.
Payments, cards, lending journeys, fraud and transaction testing.
Policy, claims, underwriting and workflow testing.
Patient workflows, claims, integrations and data privacy.
Subscriptions, onboarding, APIs, commerce and customer journeys.






We'll come back with a baseline proposal: what to assess, which roles to prioritise and how capability gets measured.