AI agents

Overview

Aqili Next is agent-native: AI is woven through the product rather than bolted on. A Copilot answers questions and drafts work from your live data, and a set of specialist agents handle recurring AR tasks. The defining rule is simple and applies everywhere.

Agents propose, humans approve

No agent changes your data on its own. Agents read live data and draft proposals; a person reviews and approves before anything is applied. Every run — what the agent saw, proposed, and did — is recorded in History so it can be audited and replayed. This is what makes AI safe to use on financial data.

The Operator Copilot

Ask in plain language — “who's more than 60 days past due at Garage B?” — and the Copilot answers from live data, showing the evidence behind the answer. When you ask it to do something that would change data, it produces a proposal you approve rather than acting silently.

Specialist agents

• Collections — works your aging, drafts follow-ups and escalations for past-due accounts.
• Reconciliation — proposes applications for unmatched or partial payments.
• Onboarding — assists with importing and validating data during migration.
• Late-fee review — reviews fee application against policy and flags exceptions.
• Audit — surfaces anomalies across billing runs and payments for a human to confirm.

Approvals and audit

Proposed writes land in an Approvals queue with the context behind them. Approve, edit, or reject. Approved actions apply immediately and are logged; rejected ones are recorded too, so you have a complete trail of what the agents suggested and what your team decided.

How agents use your data

Agents operate strictly within your tenant — they can only see your data, enforced by row-level security. We configure our AI providers to disallow training on Service data, and we do not use your data to train third-party general-purpose models.