MindBridge
Scores every general-ledger transaction for risk so audit and finance teams review the outliers, not a random sample.
- Starting price
- Contact sales
- Pricing
- Contact sales
- Pricing checked
- October 12, 2026
Our take
- Best for
- External audit, internal audit, and controller teams that need a risk rank on the whole general ledger instead of a random journal-entry sample.
- Not ideal if
- A firm that needs the engagement file, the close checklist, or a tie from a PDF to Excel. MindBridge does not keep the books and does not assign close tasks.
- Standout
- Every imported ledger line gets a risk score and the control points behind it, so journal-entry testing starts at the outliers.
About MindBridge
MindBridge scores the general ledger you give it. You import the GL, usually an Excel or CSV export from the accounting system, confirm the account mapping, and it runs machine-learning, statistical, and rule-based tests on the full set of entries rather than a sample you picked first. Each transaction gets a risk score and the tests that fired. Auditors use that queue for journal-entry testing, including an interim file before year-end, and can add selections to an audit plan and export them. Finance and internal audit can import periods on a schedule and watch a risk queue through the year. Libraries exist for for-profit and not-for-profit ledgers. MindBridge does not post the entry and does not lock the period. The books stay in the system you exported from.
DataSnipper traces a sample back to a PDF in Excel. MindBridge does not read the invoice. It tells you which lines are worth opening. FloQast and Numeric run the close checklist, the reconciliations, and the sign-off. MindBridge does not assign those tasks. NetSuite can still be the ledger. The pages reviewed here did not name QuickBooks Online, Xero, or NetSuite as connectors. The documented path for a standard GL analysis is a file import. API and data-platform pipes (Databricks, Snowflake, Azure Data Factory, Microsoft Fabric) are how larger teams send data in without a manual upload.
Teams keep it when a random journal-entry sample is the weak step. A reviewer starts with the high-score lines, sees which control points fired, and can explain why those lines were tested. Firms that want coverage of the whole population, and a reason on each flag, are the ones who stay. The close calendar is still a different product.
Pricing
No public price and no pricing page. The path on the site is a demo form. A sales brochure says pricing is predictable and that a multi-year price lock is available. It does not list a dollar amount. API access is a separate requirement for the Azure Data Factory import. The same brochure's platform-investment figure is not a funding total and is not listed here. A shop that only needs to categorize a bank feed is not the buyer.
Custom
Audit firms and company finance teams that want every ledger line scored. Sold by demo. No public price.
- Full-population general ledger risk scoring
- Journal-entry selections with the tests that fired
- Interim, full-year, and periodic imports
- API and data-platform feeds where you buy API access
How it hits your books
- Replaces your ledger
- No
- Multi-entity
- Partial
- Inventory
- No
- 1099s
- No
- Payroll
- No
You can score an interim or periodic ledger export before year-end. MindBridge does not reconcile accounts, route journal entries, or lock the period. That still happens in the ERP.
Export the selected entries and the control points that fired. That supports journal-entry testing. It is not a trial balance package or a tax file.
Features
- Score the whole general ledger
- Import an Excel or CSV general ledger, plus opening and closing balances when you need trends or a balance sheet. MindBridge maps accounts to its codes and you verify the map. The GL analysis scores every entry with machine-learning, statistical, and rule-based control points. It is aimed at balanced transactions with two or more lines.
- Test journal entries from the high scores
- Stratify selections toward high or medium risk, drill into a control point such as flow analysis, add the lines to an audit plan, and export a sheet that lists the transaction and the control points that fired. The general-ledger product page says the platform uses 32 algorithms and can slice by cost center, region, legal entity, or a field you configure.
- Run interim, full-year, or periodic files
- A GL analysis can be a full period, an interim file you later convert when the year is complete, or sequential periods imported on an ongoing basis. A risk monitoring dashboard, if an admin enables it, compares summary analytics between two date ranges. You still close the period in the ledger.
- Use a library that matches the entity
- Documented GL libraries are for-profit, not-for-profit, and not-for-profit with fund. A separate review-engagement analysis uses the same families of tests to support a review opinion. Transaction Risk Analytics is a configured add-on for card, payroll, revenue, or vendor datasets, built with a MindBridge customer value architect.
- Feed it from a data platform
- The integrations page names Databricks, Snowflake, Microsoft Fabric, and Azure Data Factory. The Azure path posts JSON to MindBridge's API and requires API access. The developer materials describe a large endpoint set, webhooks, and a Python SDK. A manual Excel upload remains the documented path for a standard GL analysis.
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Integrations
Platforms
Audience
Pick something else instead of MindBridge
DataSnipper
Pick DataSnipper instead if the next step is tracing a sample to source PDFs in Excel, not ranking the ledger.
FloQast
Pick FloQast instead if you need the close checklist, reconciliations, and journal approval on the ERP.
Numeric
Pick Numeric instead if the job is month-end tasks and flux on QuickBooks Online, Xero, or NetSuite.
Ready to try MindBridge?
Check the live pricing page before you sign up. Plans change.