We run it ourselves
Built on the platform our own GTM team runs on.
The same agent platform we operate in production at monō. Finance is in early access on it now, come and talk to us about running it.
Think of it as your agentic cfo.
Forecasting, budgeting, reporting and cash, run by agents that live in your ledger, your bank feeds and your board pack.
Everything, one place
Replaces
Spreadsheet sprawl
Replaces
FP&A point tools
Replaces
The month-end scramble
01
Financial Forecasting
Rolling forecasts rebuilt continuously from actuals, pipeline and drivers. The number moves the moment the inputs do, and explains why it moved.
02
Budgeting & Planning
Agents draft, negotiate and track budgets with every owner, not in fourteen spreadsheet versions. Variance explained in plain language before you ask.
03
Revenue Intelligence
Continuously reconciled from your ledger and billing systems. Know why the number moved, not just that it moved.
04
Cash & Collections
Agents track cash position and runway daily, chase receivables in your tone, and flag risk while it's still cheap to fix.
05
Board & Investor Reporting
Board and investor reporting assembled from live data, every number traceable to source. You add the judgement.
06
Ask Finance
One question surface over forecast, budget, cash and actuals. It surfaces the decision before the deadline.
No rip-and-replace
Tile one plugs into your ERP, Xero, your bank feeds, reading, enriching, doing the work around them. Every tile after that absorbs more of the work.
The quiet ending
One day you notice the old system is just an archive.
Autonomy
The forecast rebuilds itself.
The board pack drafts itself.
Your copilot surfaces the decision before the deadline.
CFO Copilot
Surfaces the decision before the deadline.
Time to value
Days 1–3
Connected to your systems. Agents reading, learning your context.
Week 2
First tiles live in production. Real work, measured.
Always
Every customer is paired with a forward-deployed engineer.
Proof
We run it ourselves
Built on the platform our own GTM team runs on.
The same agent platform we operate in production at monō. Finance is in early access on it now, come and talk to us about running it.
Architecture
Your ledger stays the system of record.
Finance sits on top, reconciling and reporting around it. Nothing is ripped out to get value.
Every frontier model, no lock-in. 100+ connectors. Semantic memory. Sovereign by design, your cloud, your keys, and everything your agents learn stays inside your walls.
Built with
Finance runs one function. Running agents across your whole business?
Go AI-native with monō for EnterpriseTrust & governance
Governed. Measured. And you can see exactly what it costs.
monō does the same work for a fraction of the spend. It only sends the AI what it actually needs to answer, not the whole history. So a typical task can use up to 70% fewer tokens than running an agent the standard way. Routine, high-volume work runs on cheaper models; the hard calls go to the best models available. And for the work you do most, we tune smaller, faster models built for the job.
You see the cost per agent, in plain numbers.
Governance
Every agent runs under policy. Every action logged, reproducible and reviewable.
Eval & monitoring
Every output scored against your standard before it ships. Drift caught early.
Cost & efficiency
Far fewer tokens than running an agent raw, and the right model for each job.
The pack your risk team will ask for.
Deployed in your cloud. Inference-only, your data is never training data. ISO 27001 certified. The controls map, data-flow diagrams and sub-processor list.
PDF · 4 pages
In your industry
On your infrastructure or your private tenancy. monō is inference-only by architecture, your numbers never train anyone's models and never leave your control.
No. Finance sits on top of your ledger, bank feeds and spreadsheets from day one, reading, reconciling, doing the work around them. Retire what it replaces when that's earned.
Early-access cohorts go live in weeks, paired with a forward-deployed monō engineer through activation.
One agentic use case, productised, Financial Forecasting is a Tile. A Collection is the set of Tiles that runs the whole function.
Yes, that is the point. Every Tile writes to one shared memory, so the next one starts smart: it already knows your accounts, your people and your numbers. Run another collection and it inherits all of it. The Ask tile is that memory, answering.
Yes. Bring your own API keys, they work across every agent and every collection, and you pay the lab exactly what you'd pay them anyway. No markup.
Materially less than pointing a frontier model at the same work raw. The harness sends only the relevant context, checks memory before re-reading, and routes volume work to smaller models.
Collections are licensed per company, not per seat. Talk to us.
Finance is in early access. Request early access and see it on your own data.