Datarails

Datarails doesn't ask your team to abandon the spreadsheet. Existing workbooks stay in place and pull from the connected data layer, so models built over years keep working. Budget managers submit through web forms, and reviewers approve without passing files around.

The platform handles financial consolidation: it maps general ledger accounts, departments, and cost centers to your reporting structure once, then runs intercompany eliminations, currency translation, and multiple charts of accounts automatically, which is where most multi-entity teams lose days every month.

You can ask questions in plain language, run agents for recurring analyses, and build custom agents for your own workflows. The answers rest on consolidated, reconciled data rather than a raw export, which is the difference between a figure you can take to a board meeting and one you have to check first.

This connector links governing financial data to outside AI tools such as Claude. Permissions and an audit trail travel with the data, so an analyst can use a general assistant without pasting the general ledger into a chat window.

The month-end close module puts checklists, reconciliations, task assignments, and sign-offs into one place with an audit trail. Each entity's status is visible, so a controller spends less time chasing confirmations by email.

The Cash module syncs bank balances, shows positions across accounts and currencies, and projects a rolling forecast. Treasury can drill into a variance instead of waiting for a month-end report to explain what happened.

Requests, purchase orders, invoices, and corporate cards connect back to the budget, so you see the impact on plan before money leaves the account. Approval routes and coding rules run as workflows rather than reminders.

Reporting, dashboards, and custom report builders pull from the same dataset. AI Storyboards turns dashboard output into an editable presentation for leadership, which cuts the manual slide assembly before each board meeting.