Continuous Assurance & Controls Monitoring
Always-on control monitoring instead of periodic samples
Learn more →We design and build continuous, AI-driven assurance solutions for internal audit and wider assurance functions in regulated financial services – replacing manual, point-in-time testing with always-on coverage, built by an FCCA-qualified auditor with an MSc in Data Science
Pick the one that sounds most like you – we'll show you where we'd start, and a no-cost way in
We find the highest-value uses across your audit lifecycle – document and policy review, fraud indicators, risk assessment, QA and reporting – and build them to run in a regulated environment, with a human in the loop
A working session mapping where GenAI would pay off first in your function
We help audit teams take the first steps: quick wins that build confidence, a practical roadmap, and hands-on training so the capability stays with your people, not with a contractor
A no-pitch conversation with your auditors, plus a starter roadmap for where to begin
We review what's already been built – for value, control weaknesses and key-person risk – govern the self-service estate, and unlock the use cases the licences were bought for in the first place
A review of what you've built and where the value – and the risk – is hiding
We design and build continuous controls monitoring – data feeds blended and scored, exceptions flagged and routed to the right auditor automatically – so you move from a sample to the full population
We pick one control and map exactly what always-on coverage would take
A short, no-obligation conversation about your controls, your data and your team. We'll tell you honestly where analytics and AI would move the needle – and, just as usefully, where they wouldn't.
Fifteen minutes to work out whether there's a fit. No slides, no pressure
Continuous assurance doesn't test harder – it tests everything, all the time, and sends only the exceptions to a human. Same team, complete coverage.
Four delivery lines plus two advisory lines that govern the tools you already have and turn stakeholder engagement into risk intelligence.
Drawn from delivery inside a large regulated financial-services firm. No client, system, dataset or document is ever named, reused or repurposed. Case studies are published in de-identified form only.
A short, no-obligation conversation about your controls, your data, and where AI and automation would actually move the needle