Introducing FloQast Detect: AI-Powered Anomaly Monitoring for a Cleaner Close

This is part of a series of posts on the new capabilities FloQast announced at TakeControl 2026. For the full picture — including new Transform building capabilities, journal entries reviewed by the AI Assistant before they post, Detect, and Operational Audits — check out the complete TakeControl 2026 announcement here.

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This is a pretty standard accounting experience: anomalous transactions discovered late, investigated manually, explained retroactively, and documented in ways that may or may not survive the next audit. The close gets slower. The team gets more stressed. And next period, it happens again.

FloQast built Detect to break that cycle.

AI That Learns Your Books, Not Generic Rules

Most transaction monitoring tools rely only on rules. You might tell the system to flag anything over $X or catch postings to certain accounts. But rules can only catch what you’ve defined in advance, not account for the actual shape of your business. A $500,000 transaction might be completely normal for one subsidiary and wildly unusual for another. A rule can't tell the difference.

This is where AI-powered detection monitoring adds another layer. FloQast Detect continuously monitors your GL data and learns what normal looks like for each account and subsidiary. When a transaction falls outside those learned patterns, it gets flagged. Not because it violated a predefined rule, but because it doesn’t fit the patterns in your data.

That distinction matters. Rules look for issues you’ve already defined. AI uncovers anomalies you might never think to check for.

Rules Defined by You, Not By a System

AI models learn from data. But your team carries institutional knowledge that no model can derive on its own: policies, precedents, business logic specific to your organization.

Detect includes a user-defined Rules layer that sits on top of the AI model. Teams can codify that knowledge and apply it consistently across every transaction, every period. The rules and the AI work together: one catches what you knew to look for, the other catches what you didn't. Together, they cover the gap that either alone would leave open.

Continuous Monitoring, Not Only at Month-End

Detect doesn’t just catch what manual monitoring misses. It does it before it becomes a close problem. 

Detect continuously monitors GL data, surfacing anomalies in near real-time as transactions are recorded. Instead of waiting until month-end to uncover issues buried in the books, teams can spot anomalies as they arise throughout the period, investigate them while the context is fresh, and resolve them before they become a close-week emergency.

This shifts the entire dynamic from month-end cleanup to day-to-day data hygiene. Issues get addressed while they’re small and manageable, rather than piling up until the close, when deadlines are tight. 

A Workflow, Not Just a Notification

Getting an alert that something looks wrong is only useful if the right person is notified to take action. 

Detect routes flagged transactions to the right assignees through a structured review, resolve, and sign-off workflow. With ERP source records surfacing in-context alongside the transaction in FloQast, assignees have everything they need to act without toggling between systems. 

Every detection, comment, and sign-off gets captured in a full activity log as it happens. When your auditor asks what happened with a flagged transaction from six weeks ago, the answer is already there: timestamped, attributed and complete. Nothing needs to get reconstructed after the fact.

The workflow keeps your team efficient. The activity log keeps you audit ready. 

Learn More 

Detect was announced at TakeControl 2026 and is currently in beta.

The underlying idea is straightforward: catch the problem when it happens, not when you're already deep into closing your books. Give the reviewer everything they need to resolve it in one place. Document the whole thing automatically. Controllers and accounting managers have been asking for this kind of monitoring for a long time. Detect turns that idea into a practical workflow for accounting teams.

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