For accounting teams

AI agents for accounting. Procedure included.

The numbers sit in the general ledger, in payroll, in the billing system, in Excel, and in a system you switched off two years ago. No single report has all of it, the work is manual, and the month-end close deadline does not move.

Countz has an agent for each task: reconcile the bank and the balance sheet accounts, review journal entries and transactions for errors, answer the audit requests. Each agent comes with its procedure written: what to check, how much of it, and what a discrepancy means.

The agents are free. They run on the ChatGPT or Claude subscription your team already pays for. None of your data comes to Countz.

Agents

Agents you can run today.

Each agent was built for a task a customer had to get done. If your task is not listed, use countz-analysis skill to plan it out interactively, or describe it to us and we build the agent for it with you.

Five groups of agents, by who runs them.

Reconcile the bank and the balance sheet accounts

Every discrepancy researched, with supporting documentation and the adjustments it needs.

Input: the bank statements, the trial balance, the subledgers and the supporting schedules for each account

Review journal entries and transactions for errors and anomalies

Unusual amounts, wrong coding, uncategorized transactions. Each one flagged for review, with the reason.

Input: the general ledger detail for the month, the journal entry listing, and the prior months to compare against

Audit support: answer the audit requests with supporting documentation

Built from the reports you already produce, with the open items listed.

Input: the audit requests, the reports already produced, and the detail behind each one

SOX and internal controls: assemble the evidence for each control

Including the completeness and accuracy of the reports each control relies on.

Input: the control description, the reports it uses, and the detail behind them

Prepare the accrual, prepaid and fixed asset schedules

Rolled forward from last month, depreciation and amortization recalculated, each schedule reconciled to the general ledger.

Input: last month’s schedules, open POs and contracts, the invoices that have landed, and the general ledger balances

Reconcile payroll to the general ledger

Wages, payroll taxes and benefits, with every discrepancy explained.

Input: the payroll reports, the payroll journal entries, and the accrual and liability accounts
Example

“The seller has eleven add-backs to EBITDA. How many of them are real?”

Files Countz read

  • Three years of GL detail and the trial balances behind it
  • The bank statements for the same period
  • The seller’s add-back schedule and the memos under it
  • Contracts, invoices and the receivables aging

Procedure Countz ran

  • Rebuilt EBITDA from the entries, month by month, for all three years
  • Tested each add-back: does it recur, and is there a document behind it
  • Traced revenue to cash and rebuilt working capital by month

Result Countz delivered

  • A bridge from reported to adjusted, each step tied to its entries
  • Seven add-backs supported, three that recur in all three years, one with nothing behind it
  • Customer concentration and retention computed from the invoices
  • A list of what could not be tested, and why
How it works

Install, upload your reports, review the result.

How Countz runs, in three steps. 1. Install the Countz plugin, in Claude or ChatGPT Work. No change needed in your systems. 2. Ask for the work: type /countz, then ask in plain English, for example “diagnose any revenue leakage in FY25” with the trial balance attached. Your data stays in your AI account. 3. Review the report: every figure traces back to the source data. You decide what goes out.
Questions

Common questions.

Why not use ChatGPT or Claude on its own?

You can. Each accounting task needs its own instructions, tests on real reports and fixes for what it gets wrong, and every attempt uses part of your subscription’s usage limits. Countz has those agents already written, each with its procedure, so your time goes to the work and the review.

Nine of fourteen model runs flagged almost every clean financial statement as wrong.FinVerBench, fifteen current models tested on SEC filings from 43 S&P 500 companies, May 2026 · arxiv.org/abs/2605.29586

Where does our data go?

It stays in your AI account. None of it reaches Countz, so we hold nothing of yours to secure or delete.

Can I rely on the numbers?

The result shows which files were read and how much of each, traces every figure back to the source data, and lists what could not be reached. You review it as you would review work your own team prepared.

Will the auditor accept the result?

Auditors test what the company produces, however it was produced. The result gives them an audit trail from each figure to its source and a note of what was not covered.

What does it cost?

The agents are free. Running them uses your ChatGPT or Claude subscription like any other task you give it, and counts toward its usage limits.

Get free access

Tell us the first task you would give Countz.

Describe the task as you would to a colleague. A person reads every request and replies with install instructions.

The system, the period, when it is due, and what went wrong last time.
Or write to beta@countz.ai
Received. A person will reply with install instructions.