AI bookkeeping that shows its work.
CharFlo turns statements, receipts, and transaction data into reviewable bookkeeping proposals. Every material value keeps a path to evidence, and uncertainty is routed to people instead of hidden.
From raw records to reviewable books
CollectDocuments arriveStatements, receipts, spreadsheets, and authorized transaction history.
PrepareTransactions reconcileRecords are parsed, matched, deduplicated, and checked against control totals.
ClarifyThin evidence pausesUnknown vendors and low-signal transactions become focused questions.
ApprovePeople reviewCorrections, mappings, and outputs remain proposals until accepted.
What automation handles
- Document classification and structured extraction.
- Statement reconciliation and duplicate detection.
- Bounded categorization proposals against the chart of accounts.
- Clarification grouping for transactions that need context.
- Preparation of review-ready exports and reporting inputs.
What stays with people
- Resolving ambiguous transactions and business context.
- Approving account mappings and corrections.
- Deciding whether the evidence supports a complete financial statement.
- Approving anything shared with the client or posted downstream.
A confident guess is not clean bookkeeping.
CharFlo is designed to stop when the evidence is insufficient, ask the smallest useful question, and preserve the reviewer’s authority.
Financial reporting without invented balances
When a complete trial balance or sufficient opening data exists, deterministic tools validate mappings and construct statements. When the evidence is incomplete, CharFlo limits the output or shows the discrepancy instead of pretending the books balance.