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Solution blueprints
Finance

Invoice and statement reconciliation

Match the numbers, flag only the exceptions

A finance agent that reads vendor invoices and bank statements, matches every line against your ledger, and surfaces only the mismatches that need a human. Closes faster, with a full audit trail.

The problem

Finance teams burn days each month matching invoices, statements, and bank feeds against the general ledger by hand. The work is slow, error-prone, and hard to audit. Most lines match cleanly, so people spend their time on rote checking instead of the exceptions that actually matter.

The outcome

4x

faster month-end reconciliation

The architecture

How the work actually flows

No black box. This is the real data and agent flow, from the moment work arrives to the moment it is done, with a human in the loop wherever the stakes are high.

  1. Ingest

    Pull invoices, bank statements, and remittance files from email, SFTP, and your accounting system as they arrive.

  2. Extract

    Read each document with layout-aware OCR and an LLM into structured line items: amounts, dates, references, and tax.

  3. Match

    Reconcile every line against ledger entries with deterministic rules first, then fuzzy and embedding-based matching for the rest.

  4. Validate

    Apply your tolerance thresholds, duplicate checks, and three-way match rules so confident matches clear automatically.

  5. Review

    Route only unmatched lines and policy breaks to a finance reviewer with the evidence and a suggested resolution attached.

  6. Post

    Write cleared matches and approved resolutions back to the ledger and produce an audit-ready reconciliation file.

What we build

  • Document ingestion from email, SFTP, and accounting APIs
  • Layout-aware extraction tuned to your invoice and statement formats
  • A rules-plus-embeddings matching engine with configurable tolerances
  • An exception queue with evidence, suggested fixes, and one-click approval
  • Write-back to the ledger and an exportable audit trail

Representative stack

Python LangGraph Document AI Anthropic Claude pgvector Temporal Postgres

We choose tools to fit the job and your constraints. We are not tied to any one vendor.

Let's adapt this blueprint to your systems

Take the assessment. We start from this reference and tune it to your data, your tools, and your bar for quality.