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This functionality is actively evolving. Please check back regularly for updated content.

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Continuous bank account reconciliation

Tight automatically pulls account balances on an ongoing basis and validates them against the corresponding General Ledger balances to detect discrepancies as early as possible. Additionally, once bank statements are available, Tight programmatically ingests these from the underlying bank integration and parses out the relevant dates, balances, and individual transactions to automatically perform the monthly reconciliation process per linked bank account. Through these two types of automated reconciliations, Tight removes the manual labor that is required in legacy accounting systems to perform monthly bank account reconciliations.

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Agentic book closings

Tight Agentic Accountant performs book closings on a recurring basis (monthly, quarterly, and annual) and provides financial summaries for the closed period. Business owners can review these summaries and subsequently converse with the agent about their company’s books, including making modifications when needed.
The timing of agentic closings can be configured in the company’s AI settings

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CFO-level trend analysis

Tight Agentic CFO is trained to provide CFO-level trend analysis using the business’s historical financial data. Business owners receive performant real-time replies on interesting trends across all of their historical data, including data imported from QBO, Xero, and Wave, beyond the capabilities of most human beings.

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Anomaly detection

Tight Agentic Bookkeeper reviews General Ledger balances ongoing to detect anomalous transactions. Tight Agentic Bookkeeper surfaces these transactions to the end-user along with a proposed modification to clear the anomaly if necessary. This enables users to keep a close eye on their business without reviewing every single transaction.

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Conversational reasoning

When Tight’s categorization engine is unable to categorize a transaction with sufficient confidence, Tight Agentic Bookkeeper reaches out to the end user with questions about the transaction, e.g., “Did you meet with a client for this Starbucks charge?” The end user is able to reason with the agentic accountant via a conversation to categorize and reconcile the transaction.