A Double-Entry General Ledger With AI on the Keys
Fintra’s AI drafts the categorization for every transaction and a person approves it - so the books stay proper double-entry, close-ready, and never a month behind.
Illustrative product view
What the AI general ledger in Fintra does
The general ledger is the system of record everything else in finance reports from. Fintra rebuilds it AI-native: it keeps rigorous double-entry accounting, but instead of a bookkeeper coding transactions in a weekly queue, AI drafts the categorization for each one and a person approves it. The result is books that stay current daily rather than being reconstructed in a monthly scramble.
- Proper double-entry accounting - every entry balances debits and credits
- AI categorization of transactions against your actual chart of accounts
- Human approval before anything posts, with low-confidence items queued for review
- A continuously current ledger that feeds budgeting, forecasting, and the close
Core capabilities
| Capability | What it does | What it replaces |
|---|---|---|
| Double-entry core | Enforces balanced debits and credits on every posting | Single-entry apps that don’t truly tie out |
| AI categorization | Codes transactions to the right accounts from context and history | Manual bookkeeper coding queues |
| Approval gate | Holds AI-drafted entries for human sign-off before posting | Auto-posting you can’t inspect |
| Confidence routing | Sends low-confidence items to review instead of guessing | Silent misclassifications |
| Continuous close | Keeps the ledger close-ready every day, not just month-end | A four-week catch-up close |
How AI categorization with approval works
From raw transaction to posted entry
- 1
Ingest the transaction
Bank feeds, bills, expenses, payroll, and invoices flow into the ledger from the modules that created them.
- 2
Draft the coding
AI proposes the account, class, and any splits from the transaction’s context and how similar ones were coded before.
- 3
Score confidence
High-confidence, in-pattern entries are ready to approve; anything ambiguous is routed to a review queue with the reason.
- 4
Approve or correct
A person approves the batch or fixes a coding; every correction trains the categorizer on your preferences.
- 5
Post double-entry
Approved entries post as balanced double-entry journal lines, and the audit trail records who approved each one.
Governed AI, not autopilot bookkeeping
An AI that posts to your ledger unsupervised is a liability, not a feature. Fintra’s ledger is governed: AgentFence policy lets the categorization agent draft and suggest, but posting to the books requires human approval. Every entry carries who approved it, what the AI proposed, and when - so the ledger is defensible line by line.
- AgentFence bounds the categorization agent to drafting - not posting on its own
- The SentriAI-powered audit trail records the AI’s proposal and the human decision for each entry
- Corrections are captured as evidence and improve future categorization
- Because the ledger is always current, the month-end close becomes a review, not a rebuild
How it connects to the rest of Fintra
- Bill pay, expenses, payroll, commissions, and equity all post into this one ledger
- Budget vs actuals reads live from the ledger, so plans track reality daily
- Forecasting inherits real run rates and payment timing straight from the books
- Financial close works from an already-current ledger instead of a backlog
Frequently asked questions
Is Fintra’s general ledger real double-entry accounting?
Yes. Every posting balances debits and credits, so the ledger ties out the way an accountant expects. The AI-native part is how transactions get categorized - drafted by AI and approved by a person - not a shortcut around double-entry itself, which stays fully intact underneath.
Does AI post entries to the books automatically?
No. AI drafts the categorization for each transaction, but posting to the ledger requires human approval. High-confidence, in-pattern entries are quick to approve in a batch, and low-confidence items are routed to a review queue rather than guessed, so nothing lands in the books without a person’s sign-off.
How accurate is AI transaction categorization?
Fintra codes against your actual chart of accounts and learns from every correction you make, so accuracy climbs with use. Just as important, it flags what it’s unsure about instead of hiding it - the audit trail shows exactly which entries were AI-drafted versus human-corrected, so accuracy stays inspectable.
What is a continuous close and how does the ledger enable it?
A continuous close means the books stay close-ready every day instead of being caught up once a month. Because transactions are categorized and approved as they arrive, the ledger is already current when the period ends - so the close becomes a review and sign-off of work already done, not a multi-week reconstruction.
Stay in the loop
One practical finance briefing a week - new guides, checklists, and benchmarks.
Keep the books current, every day
Start free, no card required. Let AI draft the coding and approve entries with one review.
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