NineAnts · Treasury AI Agent
Treasury AI agent: agentic AI that keeps treasurers in control
A treasury AI agent is software that analyses your cash data, forecasts cash flows and recommends actions on liquidity, funding and FX. The NineAnts Treasury AI Agent uses deterministic and statistical tools, such as an excess cash optimiser, a cash shortage detector and an FX exposure analyser, logs its reasoning, and leaves anything that moves money to your team.
- Same inputs, same outputs, every time
- Deterministic
- Excess cash, cash shortage, FX exposure
- 3 treasury tools
- Every recommendation back to the numbers
- Traceable
- Your team decides on anything that moves money
- Human-led
The problem
Forecasts that nobody acts on
A cash flow forecast is a starting line, not a finish line. Its purpose is to spot risks and opportunities early enough to act. In practice, most teams spend so long building the forecast that there is little time left to use it. Surplus cash stays in current accounts. Funding gaps are noticed weeks later than they could have been. Currency mismatches show up in the P&L instead of in a hedge.
Generic AI does not solve this. A general chatbot does not understand treasury, cannot be audited, and may give a different answer to the same question tomorrow. Treasury needs an assistant it can check.
How NineAnts does it
How the Treasury AI Agent works
A language model understands the question. Deterministic treasury tools do the maths. Your settings decide what the agent may do on its own.
A language model as the orchestrator, treasury tools as its hands
At the centre of the agent is a large language model. It does not do the maths itself. It understands your question, retrieves the relevant data, chooses the right tool, interprets the result and explains it in plain language.
The tools are deterministic and statistical, built for treasury work: forecasting models chosen per cash flow category, an excess cash optimiser that finds surplus liquidity and how long it will last, a cash shortage detector that finds funding gaps before they happen, and an FX exposure analyser that finds currency mismatches in the forecast. The same inputs give the same outputs, every time.
Every recommendation is traceable
The agent logs its reasoning. Every recommendation can be traced back to the numbers and methods that produced it, and every action can be reproduced by a person without the agent.
Every AI-generated entry in a forecast is marked, so you always know which numbers came from the AI, which from connected systems and which were entered by hand.
Autonomy you configure per action
Autonomy in NineAnts is not a single on/off switch. You set it per action type: generating a forecast, writing a prediction into a category, adjusting existing entries, running scheduled jobs, sending notifications. For each one, the agent may act on its own, must ask for confirmation first, or may not perform the action at all.
Most teams start in a review-first posture and allow more as confidence grows. Treasury stays in control of anything that moves real money.
Questions a forecast tool cannot answer
A procedural tool runs a model when you press a button. The agent follows a different path depending on the question. Ask for a forecast and it builds one. Ask "why were our supplier payments so high in March?" and it pulls the actuals, compares them with historical norms, identifies the outlier transactions and explains what happened.
Ask it to apply a scenario, such as customer receipts 20% lower next quarter, and it recalculates the forecast on top of your base case.
From assistant to team member
The agent does not only answer when asked. It can run on a schedule: produce the weekly forecast before the team arrives on Monday, compare actuals with forecast at the end of the week, and alert the team when excess cash crosses a threshold. It does the work and reports back.
A quality check on every submitted forecast
In groups where subsidiaries contribute to the forecast, the agent reviews each submission against historical patterns and flags anomalies. A subsidiary whose supplier payments are 40% below the same period last year, with no change in receipts, gets a question before the numbers reach the group forecast.
What you get
Decisions earlier, with the reasoning attached
- Early sight of excess cash, with the amount and how long it is available
- Early warning of cash shortages, weeks before they hit
- FX exposure found in the forecast, before it hits the P&L
- Plain-language answers to treasury questions, based on your own data
- A logged, reproducible reasoning trail for every recommendation
- Autonomy set per action type, from fully manual to review-and-approve
- Scheduled jobs and alerts without anyone pressing a button
- Automatic checks on forecasts submitted by local teams
Why it can be trusted
Built on clean, categorised history
- historical transactions learned from in one implementation
- 181,031
- agreement with the team's own categorisation
- 99.3%
- less manual categorisation work
- 67%
An agent is only as good as the data it reasons over. Before the Treasury AI Agent forecasts anything, NineAnts learns the client's categorisation logic from their own history.
In one recent implementation, the resulting rule set categorised 89% of transactions automatically, up from 58% with the team's Excel formulas. The team still manages the rules; the repetitive daily work is largely gone.
One platform
How it connects
The agent works on top of the rest of NineAnts. The Treasury AI Agent is included in the Enterprise plan, together with cash flow forecasting. See pricing on the NineAnts page.
- Keeps it fresh
Data automation
Feeds it fresh bank and ERP data every day, and puts the results in your own workbooks.
Learn more - Gives it the position
Cash visibility
Gives it today's position across every bank, entity and currency.
Learn more - Teaches it
Transaction categorisation
Gives it clean categories to learn from.
Learn more - Gives it the forecast
Cash flow forecasting
Gives the agent the forecast to analyse and act on.
Learn more - You are here
Treasury AI Agent
Finds excess cash, shortages and FX exposure, and shows its working.
Want to go deeper on agentic AI in treasury? Read Part II of our guide: The AI.
Built security first
Frequently asked questions
Straight answers to the questions treasurers ask us
What is an AI agent in treasury?
An AI agent in treasury is software that can analyse cash data, choose the right method for a question, and recommend or carry out actions within limits you set. Unlike a chatbot, it works with your actual bank and forecast data. The NineAnts Treasury AI Agent uses deterministic treasury tools for forecasting, excess cash, cash shortages and FX exposure, and logs every step.
What is agentic AI in treasury?
Agentic AI means the system decides which steps and tools a task needs, instead of running one fixed procedure. In NineAnts, a language model acts as the orchestrator. It picks forecasting models per category, runs the excess cash optimiser or FX exposure analyser, interprets the results and explains them. It can also work proactively on a schedule, within the autonomy you allow.
Is autonomous treasury safe?
It is safe when autonomy is limited and every action is traceable. In NineAnts you set autonomy per action type: the agent may act alone, must ask for approval, or may not act at all. Its tools are deterministic, its reasoning is logged, and every action can be reproduced by a person. Anything that moves real money stays with your treasury team.
How is the NineAnts agent different from ChatGPT or other generic AI?
Generic AI does not understand treasury and does not guarantee the same answer twice. The NineAnts agent uses a language model only to orchestrate. The calculations are done by deterministic and statistical treasury tools, so the same inputs give the same outputs. It works on your own bank and forecast data, inside our Azure environment, and your data is never used for training.
Can the Treasury AI Agent execute payments or investments?
Today the agent recommends and the treasurer decides. It can find excess cash, flag a coming shortfall or show an FX exposure, but anything that moves money stays with your team. You configure per action type what the agent may do on its own, such as generating forecasts, running scheduled jobs or sending notifications.
How does the agent explain its recommendations?
The agent logs its reasoning for every recommendation: which data it used, which tool or model it chose and why, and what the result was. You can trace each recommendation back to the underlying numbers, and a person can reproduce it without the agent. AI-generated forecast entries are also marked, so they are never confused with data from your systems.
Which NineAnts plan includes the Treasury AI Agent?
The Treasury AI Agent is part of the Enterprise plan, which starts from €24,000 per year and also includes cash flow forecasting, up to 20 API or SFTP integrations and up to 20 users. The Starter and Professional plans cover connectivity, automation and data delivery to Excel, Power BI and other systems.
Related reading
Podcast
Episode 295 · Mariam Halfhide · 50 min
Leaders Think AI Will Save Them, But They Are Losing Control Without Human Skills
Mariam Halfhide advises leaders on data and AI strategy. She argues that the skills worth investing in are the ones AI cannot do, and that treating governance as an afterthought is how adoption stalls.
Listen to the episodePodcast
Episode 298 · Tracey Knight · 76 min
How Treasury Teams Automate Too Late and Rely on Spreadsheets Despite AI Growth
Tracey Knight has spent thirty years in and around corporate treasury. She explains when a company should first invest in treasury technology, and how to run a vendor demo that shows you what you actually need to see.
Listen to the episodePodcast
Episode 293 · Marianna Polykrati · 38 min
AI in Treasury for Finance Leaders to Boost Forecast Accuracy by Cleaning Data
Marianna Polykrati automates everything she can, but not the cash flow forecast. She explains why automating a bad process only produces bad results faster, and what she learned connecting bank APIs in Greece.
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Put the Treasury AI Agent to work on your own data
Book a 30-minute session. We will ask about your forecasting process and where decisions get stuck, and show you what the agent would flag.