AI operating system · Finance
Finance with less manual work and forecasts the leadership team trusts
Document processing, reconciliation support, cash-flow forecasts, anomaly detection and budget narratives run through AI, with accuracy controls and a person signing every number that leaves finance.
Use cases
Where we start in finance
The cases below are the usual first candidates; the bootcamp picks yours by gain and data readiness.
- Document processing: Invoices, receipts and contracts read, classified and validated, with exceptions routed to a person.
- Forecasting: Cash-flow and revenue forecasts drafted from your history and pipeline, explained line by line.
- Anomalies in payments: Unusual transactions and duplicates flagged before they close the period.
- Budgeting and variance: Budget drafts and variance explanations prepared for the monthly review.
- Policy and reporting: Management reports and commentary assembled from the numbers finance already has, signed by the finance lead before they go out.
What we measure
The metrics agreed before the first pilot
Each pilot starts with a baseline; what we publish as a gain is what the pilot measured.
- Hours per month on primary documents and reconciliation
- Days to close the month
- Forecast error against actuals
- Anomalies caught before period close
- Share of reports delivered on the agreed date
The path
Five phases, on your own data
Every phase runs with the people who own the function; nothing leaves your perimeter without a rule.
Phase
What happens
Pre-brief
One week: the ERP, the ledgers and the reporting calendar in scope.
Bootcamp: why and where
Two days with the finance leads: where AI pays off from documents to forecasts, and in what order.
Use-case labs
Four to six weeks on your own documents and numbers: the cases that matter, tested.
Pilot sprint
Six to eight weeks: two to four pilots inside your ERP and reporting tools, with a measured result.
Scale and governance
Two weeks: the rollout plan, the accuracy controls and data policy, the approved tools, the owner.
What the function keeps
An operating system, with an owner
We install
What it gives you
AI capability map and roadmap
Where, how and in what order, for 3, 6 and 12 months.
Operating cadence
A weekly pilot review and a monthly review of the function's AI metrics, each with an owner.
Roles and ownership
A named owner of AI in the function, champions in the team, and who signs off what before it reaches a customer, a candidate or a number.
Playbooks and prompts
The working cases documented so the next person runs them the same way.
Governance and guardrails
A usage policy, approved tools, data rules, human validation where the output needs it, a risk register.
KPI set and dashboard
Adoption, time saved, quality and cost per use case, on a dashboard in your own tools, reviewed monthly.
Trained people
The team runs the working cases without us by the end of the rollout.
Formats
Where to start
AI self-check
See whether AI in your functions has an owner, a policy and a measured result, with the first moves by email within a day.Free, inside the maturity assessment
Learn moreAI operating system for finance
Install AI in finance with owners, guardrails and a measured first pilot.Fixed fee. Request a quote
Request a quoteBootcamp for finance
Two days with the finance leads: the use-case shortlist and the first pilot plan.Fixed fee. Request a quote
Request a quoteFAQ
Questions leaders ask first
Every number that leaves finance is signed by a person; the controls, the audit trail and the exceptions routed to a reviewer are part of the pilot.
Find where AI pays off in finance first
A discovery call about your processes, your data and the first pilot.
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