--- title: "Docsumo" type: "AI Tool" url: "https://aidemos.com/tools/docsumo" description: "We extracted invoices and bank statements in Docsumo; tables, totals, and metadata were solid, but missing bank sections and one field map need QA." category: "productivity" website: "https://docsumo.com/" published: "2026-08-26T07:19:19.920285+00:00" updated: "2026-08-29T15:13:21.202859+00:00" --- # Docsumo Schema-driven invoice and bank-statement extraction with strong tables and totals, but bank sections and one field map need review. ## TL;DR Verdict **Useful for reviewable finance extraction, not fully automatic** **Where it wins:** - You need invoice or bank-statement data extracted into a reviewable field-and-table UI. - You want strong line-item and transaction capture with totals that can be checked by a human reviewer. - You are comfortable building custom fields manually in Field Settings one at a time. **Main limitation:** You need native natural-language querying over extracted documents; it was not demonstrated. **Pricing:** Free $0 (14-day trial) · Business Custom (Talk to sales) · Enterprise Custom (Talk to sales) `Invoice + bank` · `Table extraction` · `Manual review` · `Custom fields` **Website:** [Visit Docsumo](https://docsumo.com/) > **Useful for reviewable finance extraction, not fully automatic** > > Docsumo is a strong fit when a human will review extracted finance documents in the UI. In these tests, core invoice and bank metadata, line items, and totals were solid, but missing bank sections, a duplicated carry-forward row, and one mis-mapped invoice field mean it still needs QA before downstream use. ## Demo Recording [Video: Docsumo demo recording](https://cdn.futuresmart.ai/public/aidemos/358df3a925724f3684be991d0ee25f9d.mp4?v=1) *Video — Screen recording of Docsumo moving from document list to field settings and then bank-statement extraction results.* ## Feature-by-Feature Breakdown ### Schema-Driven Document Field Extraction **Verdict:** Strong on core metadata, but not complete enough for unattended extraction. Docsumo extracts structured metadata and summary fields from uploaded finance documents when the user defines a schema in Field Settings. The exercised bank-statement and invoice inputs showed core account and invoice fields coming through, with a few bank-name, period, balance, and advertiser-code gaps. **Input:** Bank Statement PDF.pdf > **File** — Bank Statement PDF.pdf **Output:** image-2.png > **Image** — image-2.png **Input:** > **Pdf** **Output:** > **Image** **Input:** Invoice PDF.pdf > **File** — Invoice PDF.pdf **Output:** invoice_ss1_advertisercode_bug-2.png > **Image** — invoice_ss1_advertisercode_bug-2.png **Input:** Invoice PDF.pdf > **File** — Invoice PDF.pdf **Output:** invoice_ss4_lineitems_table.png > **Image** — invoice_ss4_lineitems_table.png **Input:** Invoice PDF.pdf > **File** — Invoice PDF.pdf **Output:** invoice_ss3_remit_flightdates.png > **Image** — invoice_ss3_remit_flightdates.png **Input:** ``` Bank Statement PDF summary fields: Total Deposits, Total Withdrawals, Total Transactions. ``` **Output:** ``` Total Deposits and Total Withdrawals matched the source exactly. The report records 70,986.83 for deposits and 69,291.02 for withdrawals, while Total Transactions failed to extract. ``` **Input:** > **Pdf** **Output:** > **Image** **Bottom line:** Reliable for core fields, but bank completeness and at least one invoice mapping still need manual review. ### Table Extraction and Row Parsing **Verdict:** Good at finding rows and columns, but repeated carry-forward lines and empty subcolumns need cleanup. Docsumo extracts dense transaction and line-item tables from documents. In the tested bank statements and invoices, it captured rows and line items, though some repeated page-break lines and subcolumns still needed cleanup. **Input:** **Output:** > **Image** **Input:** **Output:** **Bottom line:** Strong row capture, but repeated page-break rows and empty transaction subcolumns need post-processing. ### Financial Totals Extraction **Verdict:** Summary totals were accurate on both documents even when other fields failed. Docsumo extracts finance summary totals from bank statements and invoices. In the tested inputs, it populated deposits and withdrawals on the bank statement and matched invoice financial summary totals precisely. **Input:** **Output:** ``` Gross Total, Agency Commission, and Net Amount Due matched the source precisely. ``` **Bottom line:** Totals were a clear strength, even when surrounding fields needed manual correction. ## Plans listed in the report Public pricing is limited; higher tiers are quote-based. | Plan | Price | Notes | | --- | --- | --- | | Free ★ | $0 (14-day trial) | Up to 1,000 free pages, 10 user licenses, unlimited pre-trained doc AI models, fields & table extraction, webhooks/API/Excel export | | Business | Custom (Talk to sales) | Unlimited users, master data lookup, auto-classification & splitting, custom pipelines, dedicated account manager | | Enterprise | Custom (Talk to sales) | Everything in Business plus automated workflows, AI-led case management, cross-document validations, and real-time analytics | *Business and Enterprise were listed as custom plans, not public per-page or per-month pricing.* ## Is It Right For You? **Use it if** - You need invoice or bank-statement data extracted into a reviewable field-and-table UI. - You want strong line-item and transaction capture with totals that can be checked by a human reviewer. - You are comfortable building custom fields manually in Field Settings one at a time. **Skip it if** - You need native natural-language querying over extracted documents; it was not demonstrated. - You need bank statements to come back complete without cleanup; Bank Name, Statement Period, and Balances were empty. - You need raw JSON Schema import for setup; the report says fields were added manually one at a time. ## Classification - **Category:** productivity - **Subcategory:** other-productivity - **Type:** text - **Built for:** Other ## Frequently Asked Questions **Q: Does Docsumo support raw JSON Schema import for document fields?** Not in this test. The report says every field was added manually, one at a time, in Field Settings. **Q: How accurate were the invoice line items?** The invoice line-items table captured all 8 rows. Day of Week and Day Pattern were correct, but Reconciliation was empty and Reference Number looked suspicious, and Advertiser Code was mis-mapped. **Q: What failed on the bank statement?** Bank Name was missing, Statement Period failed, and the Balances section failed. The transactions table also duplicated BALANCE FORWARD across page breaks, and Value Date plus Transaction Type stayed empty. **Q: Did Docsumo split compound fields correctly?** Partially. It split Day of Week and Day Pattern correctly on the invoice, but it did not split Flight Dates into separate start and end dates. **Q: Was natural-language querying tested?** No. The test stopped at extraction and review; there was no native query or chat flow demonstrated over the extracted data. **Q: What pricing was listed in the report?** The report listed a Free plan at $0 for a 14-day trial, plus Business and Enterprise plans that require talking to sales. Business and Enterprise were quote-based. ## Similar Tools AI tools similar to Docsumo: - [Nanonets](https://aidemos.com/tools/nanonets) — Schema-first PDF extraction that produces usable exports, but dense table rows still need review. - [Retab](https://aidemos.com/tools/retab) — Schema-first PDF extraction for finance documents that returns nested JSON with minimal setup. - [Landing AI](https://aidemos.com/tools/landing-ai) — Schema-guided PDF extraction for bank statements and invoices, with strong row capture and a few identifier QA caveats. - [Datalab](https://aidemos.com/tools/datalab) — Schema-paste extraction for bank statements and invoices, with cited JSON output and fast-mode recovery when schemas get large. - [Reducto](https://aidemos.com/tools/reducto) — Hosted PDF-to-Markdown plus schema extraction with citations; strong on invoices, mixed on tables and bank statements. - [LlamaParse](https://aidemos.com/tools/llamaparse) — Versatile PDF parsing for Markdown and structured JSON, with strong recovery but some fidelity drift - [Extend AI](https://aidemos.com/tools/extend-ai) — Schema-driven extraction for finance PDFs that reconstructs nested JSON well, but still needs review for ordering, IDs, and a few scalar values. - [Unstract](https://aidemos.com/tools/unstract) — Prompt-driven schema extraction for invoices and bank statements, with strong row-level capture and a few derived-field caveats. ## Need a custom AI solution for this use case? If you are looking to build a custom invoice extraction, bank statement parsing, or structured data extraction system for your business or internal workflow, email us at [contact@futuresmart.ai](mailto:contact@futuresmart.ai). ### Found something inaccurate or missing? We try to keep our AI research accurate and useful. If you found outdated information, an issue, or have a suggestion, email us at [collaborate@aidemos.com](mailto:collaborate@aidemos.com).