For finance teams
Three ways in. Most teams start with the first.
Everything below follows the same rule: every number shows its source, a named reviewer signs off, and you keep the system when I leave. Start wherever the pain is.
The Audited AI Close
Your existing Claude or ChatGPT licence, wired into the finance function properly: scoped connectors, close workflows, a guardrail policy your CFO signs, sign-off gates, and an audit pack every close. No new software unless it's absolutely necessary.
Custom automation, measured
One process at a time: invoice flows, reconciliations, reporting pipelines. One agreed metric, measured over one month end, so the improvement is provable, not promised.
How it works What I've built, with the numbers The concrete list: 10 automations your team could run tomorrow
Your finance knowledge base, built
A knowledge base of your own documents: packs, accounts, policies, contracts. Every answer cited to the exact cell and checked, and you sign off when it passes 25 questions your own team wrote.
The Board Pack Test, on your pack
The public benchmark, run on your own board pack. You send one pack under NDA. Within a week you get a graded report: every question answered, every answer traced to its source or honestly refused, scored the same way the published exam is scored. No product access, no install, nothing touches your systems. Delivered by me, manually. Fixed scope, fixed fee, quoted when you ask.
It's the fastest way to find out what verified AI on your documents actually looks like, using the pack you already produce.
Common questions
We already pay for ChatGPT / Copilot. Why would we need you?
Good, you're already paying for the licence. Having it isn't the same as getting value from it. My job is making it safe and actually useful for the close. Almost nobody's done the wiring.
We're too small, and our processes are a mess.
Messy is the normal case, and small means we fix it faster. That's what the discovery call is for.