--- title: "Extend AI Review: Finance PDF JSON Extraction (2026)" type: "AI Tool" url: "https://aidemos.com/tools/extend-ai" description: "Ran bank statement and invoice PDFs into nested JSON with rows, totals, and confidence metadata; payment_terms leaked label text." category: "productivity" website: "https://www.extend.ai/?via=aidemos" published: "2026-07-18T11:49:23.286560+00:00" updated: "2026-07-18T11:49:23.286560+00:00" evidenceCount: 39 verifiedCount: 31 coverage: "dense" --- # Extend AI Review: Finance PDF JSON Extraction (2026) Schema-driven extraction for finance PDFs that reconstructs nested JSON well, but still needs review for ordering, IDs, and a few scalar values. ## TL;DR Verdict **Strong extraction, but not yet hands-off** **Where it wins:** - You need to extract nested metadata, summaries, and row arrays from invoices or bank statements into JSON. - You want a reviewable extraction flow with confidence metadata before export. - You can tolerate a cleanup pass for reordered sections, null transaction IDs, or label-text leakage. **Main limitation:** You need guaranteed `transaction_id` extraction on bank-statement rows. **Pricing:** Pay As You Go Free to start · Scale $500/month · Enterprise Custom pricing `Finance PDFs` · `Schema-driven JSON` · `Row extraction` · `Confidence scores` **Website:** [Visit Extend AI](https://www.extend.ai/?via=aidemos) ## Evidence (first-party, tested) *39 tested cells · 31/39 artifact-verified. Cite a cell by its Evidence ID, e.g. `ev:extend-ai·cross·advanced-features`.* | Criterion | Scenario | Verdict | Proof | Evidence ID | | --- | --- | --- | --- | --- | | Advanced Features | cross-scenario | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/181995442a5b426ab99a68c12dfeca8b.png?v=1) | `ev:extend-ai·cross·advanced-features` | | Advanced Features (Bonus) | cross-scenario | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/181995442a5b426ab99a68c12dfeca8b.png?v=1) | `ev:extend-ai·cross·advanced-features-bonus` | | Advanced Features (Bonus) | Hybrid Earnings Report | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/3c2a82256b3442c5b82d767ed5980b97.png?v=1) | `ev:extend-ai·hybrid-earnings-report·advanced-features-bonus` | | Complex Document Handling | Hybrid Earnings Report | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/07829e6dcb414445886e618cd047efb2.pdf?v=1) | `ev:extend-ai·hybrid-earnings-report·complex-document-handling` | | Complex Document Handling | Financial Report - Table Heavy | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/b12d5cd772a647818ad1833789b090d6.pdf?v=1) | `ev:extend-ai·financial-report-table-heavy·complex-document-handling` | | Complex Document Handling | Scanned Research Paper | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/45e3533a31c246b29e0ec6aaa98438e4.pdf?v=1) | `ev:extend-ai·scanned-research-paper·complex-document-handling` | | Complex Document Handling | cross-scenario | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/fe24f40fa0254094a86e301fcaed4e43.mp4?v=1) | `ev:extend-ai·cross·complex-document-handling` | | Extraction Accuracy | Invoice PDF | ✓ worked | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/research-media-extend-invoice-metadata-26a17634e0dd.png) | `ev:extend-ai·invoice-pdf·extraction-accuracy` | | Extraction Accuracy | Bank Statement PDF | ✓ worked | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/research-media-extend-ai-bank-statement-extracted-detai-ee627956b4b7.png) | `ev:extend-ai·bank-statement-pdf·extraction-accuracy` | | Extraction Accuracy | cross-scenario | ✗ failed | 👁 observed | `ev:extend-ai·cross·extraction-accuracy` | | Markdown Quality | cross-scenario | ✓ worked | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/research-media-extendai-hybrid-earnings-pdf-output-c0b21f5b9d9c.md) | `ev:extend-ai·cross·markdown-quality` | | Markdown Quality | Financial Report - Table Heavy | ✓ worked | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/research-media-extendai-financialpdf-output-826f4c89dcf6.md) | `ev:extend-ai·financial-report-table-heavy·markdown-quality` | | Reading Order & Structure | Financial Report - Table Heavy | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/1967e1c5f9944428a4dbc41122a50e81.png?v=1) | `ev:extend-ai·financial-report-table-heavy·reading-order-structure` | | Reading Order & Structure | Scanned Research Paper | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/18b2277b09fa42e3ae7a325fba02b272.png?v=1) | `ev:extend-ai·scanned-research-paper·reading-order-structure` | | Reading Order & Structure | Hybrid Earnings Report | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/873484510a8043f4aab79218961e3792.png?v=1) | `ev:extend-ai·hybrid-earnings-report·reading-order-structure` | | Reading Order & Structure | cross-scenario | ✓ worked | 👁 observed | `ev:extend-ai·cross·reading-order-structure` | | Schema Adherence | Invoice PDF | ✓ worked | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/research-media-extend-invoice-metadata-26a17634e0dd.png) | `ev:extend-ai·invoice-pdf·schema-adherence` | | Schema Adherence | Bank Statement PDF | ✓ worked | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/research-media-extend-ai-bank-statement-extracted-detai-ee627956b4b7.png) | `ev:extend-ai·bank-statement-pdf·schema-adherence` | | Schema Adherence | cross-scenario | ✓ worked | 👁 observed | `ev:extend-ai·cross·schema-adherence` | | Semantic Field Enrichment | Bank Statement PDF | ✓ worked | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/research-media-extend-ai-transaction-type-5ef541ac7fec.png) | `ev:extend-ai·bank-statement-pdf·semantic-field-enrichment` | | Semantic Field Enrichment | Invoice PDF | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/617ec8adf64f49368ea64d88d5a820cd.png?v=1) | `ev:extend-ai·invoice-pdf·semantic-field-enrichment` | | Semantic Field Enrichment | cross-scenario | ◐ mixed | 👁 observed | `ev:extend-ai·cross·semantic-field-enrichment` | | Structural Clean Output | Invoice PDF | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/416f869ecf584801a343b08e6a2734c6.png?v=1) | `ev:extend-ai·invoice-pdf·structural-clean-output` | | Structural Clean Output | Bank Statement PDF | ⚠ struggled | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/research-media-extend-ai-bank-statement-schema-order-69fcdddefcea.png) | `ev:extend-ai·bank-statement-pdf·structural-clean-output` | | Structural Clean Output | cross-scenario | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/416f869ecf584801a343b08e6a2734c6.png?v=1) | `ev:extend-ai·cross·structural-clean-output` | | Table & Record Completeness | Invoice PDF | ✓ worked | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/research-media-extendai-extracted-invoice-line-items-a11681b31146.png) | `ev:extend-ai·invoice-pdf·table-record-completeness` | | Table & Record Completeness | Bank Statement PDF | ✓ worked | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/research-media-extend-ai-extracted-transaction-item-4618ec1646be.png) | `ev:extend-ai·bank-statement-pdf·table-record-completeness` | | Table & Record Completeness | Bank Statement PDF | ✓ worked | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/research-media-extend-ai-extracted-transaction-item-4618ec1646be.png) | `ev:extend-ai·bank-statement-pdf·table-and-record-completeness` | | Table & Record Completeness | Invoice PDF | ✓ worked | 🧾 [proof](https://d3epheqghktydj.cloudfront.net/research-media-extendai-extracted-invoice-line-items-a11681b31146.png) | `ev:extend-ai·invoice-pdf·table-and-record-completeness` | | Table Preservation | Scanned Research Paper | ⚠ struggled | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/6b3fa17009604505a41ee22a883265a2.png?v=1) | `ev:extend-ai·scanned-research-paper·table-preservation` | | Table Preservation | Financial Report - Table Heavy | ⚠ struggled | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/99105bf764b54991bbcea2ecf47fbb52.png?v=1) | `ev:extend-ai·financial-report-table-heavy·table-preservation` | | Table Preservation | Hybrid Earnings Report | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/6596808a677a4687be77b6a950dfb62c.png?v=1) | `ev:extend-ai·hybrid-earnings-report·table-preservation` | | Table Preservation | cross-scenario | ◐ mixed | 👁 observed | `ev:extend-ai·cross·table-preservation` | | Text & OCR Completeness | Scanned Research Paper | ◐ mixed | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/5582cf26df374cdf98a46ff859ba1239.png?v=1) | `ev:extend-ai·scanned-research-paper·text-ocr-completeness` | | Text & OCR Completeness | Hybrid Earnings Report | ◐ mixed | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/ce874b3599394bcdb0e813ae4006d734.png?v=1) | `ev:extend-ai·hybrid-earnings-report·text-ocr-completeness` | | Text & OCR Completeness | cross-scenario | ◐ mixed | 👁 observed | `ev:extend-ai·cross·text-ocr-completeness` | | Visual Content Retention | Hybrid Earnings Report | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/ab0bf9cefafd4414a8fbc135950b69e8.png?v=1) | `ev:extend-ai·hybrid-earnings-report·visual-content-retention` | | Visual Content Retention | Scanned Research Paper | ✓ worked | 🧾 [proof](https://cdn.futuresmart.ai/public/aidemos/de1454c783be40d6ae9c9be1b56215f5.png?v=1) | `ev:extend-ai·scanned-research-paper·visual-content-retention` | | Visual Content Retention | cross-scenario | ◐ mixed | 👁 observed | `ev:extend-ai·cross·visual-content-retention` | > 🧾 = artifact-verified (proof captured) · 👁 = observed (noted, no artifact) · verdicts: worked / mixed / struggled / failed. > **Strong extraction, but not yet hands-off** > > Extend AI did a good job turning the tested bank statement and invoice PDFs into reviewable structured JSON, including nested objects, row arrays, totals, and confidence metadata. The practical caveats are clear: some top-level sections were reordered, bank-row \`transaction_id\` values stayed null, the bank summary reported 49 transactions instead of the reviewer’s expected 40, and the invoice \`payment_terms\` field leaked label text (\`Payment Terms 30 Days\`). ## Demo Recording [Video: Extend AI demo recording](https://d3epheqghktydj.cloudfront.net/extend-ai-extend-ai-8b35c2749f8e.mp4) *Video — General walkthrough of the extraction flow and output review.* ## Feature-by-Feature Breakdown ### Schema-Filled Document Extraction Populates nested document objects from user-defined JSON schemas applied to finance PDFs. In the bank statement and invoice runs, it reconstructed statement metadata, account and branch data, rewards, balances, invoice metadata, advertiser and station fields, and line-item structures. **Input:** Bank statement PDF > **File** — Bank statement PDF **Output:** Extracted bank statement JSON view > **Image** — Extracted bank statement JSON view **Input:** Bank statement PDF > **File** — Bank statement PDF **Output:** Document-level bank statement JSON view > **Image** — Document-level bank statement JSON view **Input:** Invoice PDF > **File** — Invoice PDF **Output:** Invoice metadata JSON view > **Image** — Invoice metadata JSON view **Input:** Invoice PDF > **File** — Invoice PDF **Output:** Invoice schema JSON view > **Image** — Invoice schema JSON view **Bottom line:** Very strong at filling nested document schemas, but the extracted output did not always preserve the input schema order exactly. ### Table Extraction Extracts repeating table records as discrete rows from PDFs, including financial and research tables. It kept bank-statement transactions separate, returned invoice line items with line numbers, airtimes, rates, and flight-period data, and was also tested on harder tables with grouped headers, multirow structure, and vertical annotations. **Input:** Bank statement PDF > **File** — Bank statement PDF **Output:** Bank transaction row > **Image** — Bank transaction row **Input:** Invoice PDF > **File** — Invoice PDF **Output:** Invoice line items view > **Image** — Invoice line items view **Input:** Invoice PDF > **File** — Invoice PDF **Output:** Invoice line item 6 > **Image** — Invoice line item 6 **Input:** ![landing-ai-target-annual-report-financial-summary-table-2.png](https://d3epheqghktydj.cloudfront.net/landing-ai-target-annual-report-financial-summary-table-2.png) *Image: landing-ai-target-annual-report-financial-summary-table-2.png* **Output:** ![extend-ai-target-annual-report-parsed-financial-table.png](https://d3epheqghktydj.cloudfront.net/extend-ai-target-annual-report-parsed-financial-table.png) *Image: extend-ai-target-annual-report-parsed-financial-table.png* **Input:** ![landing-ai-segment-results-table-2025-first-quarter.png](https://d3epheqghktydj.cloudfront.net/landing-ai-segment-results-table-2025-first-quarter.png) *Image: landing-ai-segment-results-table-2025-first-quarter.png* **Output:** ![extend-ai-parsed-orders-received-table.png](https://d3epheqghktydj.cloudfront.net/extend-ai-parsed-orders-received-table.png) *Image: extend-ai-parsed-orders-received-table.png* **Input:** ![extend-ai-financial-segment-reporting-table.png](https://d3epheqghktydj.cloudfront.net/extend-ai-financial-segment-reporting-table.png) *Image: extend-ai-financial-segment-reporting-table.png* **Output:** ![extend-ai-parsed-segment-reporting-table.png](https://d3epheqghktydj.cloudfront.net/extend-ai-parsed-segment-reporting-table.png) *Image: extend-ai-parsed-segment-reporting-table.png* **Input:** ![extend-ai-scanned-stand-structure-table.png](https://d3epheqghktydj.cloudfront.net/extend-ai-scanned-stand-structure-table.png) *Image: extend-ai-scanned-stand-structure-table.png* **Output:** ![extend-ai-parsed-stand-structure-table.png](https://d3epheqghktydj.cloudfront.net/extend-ai-parsed-stand-structure-table.png) *Image: extend-ai-parsed-stand-structure-table.png* **Input:** ![extend-ai-scanned-table-tree-mortality-multirow.png](https://d3epheqghktydj.cloudfront.net/extend-ai-scanned-table-tree-mortality-multirow.png) *Image: extend-ai-scanned-table-tree-mortality-multirow.png* **Output:** ![extend-ai-parsed-tree-mortality-multirow-table.png](https://d3epheqghktydj.cloudfront.net/extend-ai-parsed-tree-mortality-multirow-table.png) *Image: extend-ai-parsed-tree-mortality-multirow-table.png* **Input:** ![extend-ai-scanned-table-mountain-pine-beetle-mortality.png](https://d3epheqghktydj.cloudfront.net/extend-ai-scanned-table-mountain-pine-beetle-mortality.png) *Image: extend-ai-scanned-table-mountain-pine-beetle-mortality.png* **Output:** ![extend-ai-parsed-table-text-between-columns.png](https://d3epheqghktydj.cloudfront.net/extend-ai-parsed-table-text-between-columns.png) *Image: extend-ai-parsed-table-text-between-columns.png* **Bottom line:** It keeps rows separate well, but the bank rows still missed `transaction_id` values, so identifiers may need downstream reconciliation. ### Transaction Type Classification Infers transaction labels from description text in bank-statement rows. In the sampled withdrawal-like entries, items such as ATM usage charges, self-switch ATM withdrawal, and UPI/BILLDESK activity were labeled as Withdrawal. **Input:** Transaction description ``` 25 Jun 19 — ATM WITHDRAWAL SELF-SWITCH AT NFS 22:10:19/917622003978 00000000100000/INR 4585460013957031/362762; withdrawal amount 1000 ``` **Output:** Transaction type highlight > **Image** — Transaction type highlight **Input:** Transaction description ``` 25 Jun 19 — UPI/917615251879/ BILLDESKTEZ/BILLDESK.TNEB@ICICI/ICIC000055 5/ 0103SL001PAY/UPI/ 917615251879/; withdrawal amount 500 ``` **Output:** Transaction ID highlight > **Image** — Transaction ID highlight **Bottom line:** The classifier worked on the sampled withdrawal rows, but the report does not show a deposit example and the row IDs were still missing. ### Financial Summary Extraction Produces document-level totals and balances from financial documents. The bank-statement output included total deposits, total withdrawals, transaction count, and opening/closing balances, while the invoice output included aired spots, gross total, agency commission, payment terms, and net amount due. **Input:** Bank statement PDF > **File** — Bank statement PDF **Output:** Bank statement summary > **Image** — Bank statement summary **Input:** Invoice PDF > **File** — Invoice PDF **Output:** Invoice summary > **Image** — Invoice summary **Bottom line:** The invoice totals looked consistent, but the bank summary count and the invoice payment_terms value both show why a review pass is still needed. ### Confidence-Annotated Review Interface Displays extracted values in a reviewable interface with confidence metadata so users can validate fields before export. The report showed OCR confidence values for grouped invoice sections rather than only raw extracted JSON. **Input:** Invoice PDF > **File** — Invoice PDF **Output:** Invoice extraction confidence metadata > **Image** — Invoice extraction confidence metadata **Bottom line:** A useful validation aid, though the report only demonstrated confidence metadata on the invoice run. ### Document Structure Reconstruction **Verdict:** Strong across hybrid, table-heavy, and scanned PDFs. Reflows mixed PDF pages into readable markdown-style text while preserving headings, section flow, bullets, and nearby body content. It was exercised on a Target annual report page, a Sumitomo financial notes page, and a scanned two-column research page. **Input:** ![landing-ai-target-annual-report-growth-story-page.png](https://d3epheqghktydj.cloudfront.net/landing-ai-target-annual-report-growth-story-page.png) *Image: landing-ai-target-annual-report-growth-story-page.png* **Output:** ![extend-ai-target-annual-report-extracted-text-page.png](https://d3epheqghktydj.cloudfront.net/extend-ai-target-annual-report-extracted-text-page.png) *Image: extend-ai-target-annual-report-extracted-text-page.png* **Input:** ![extend-ai-sumitomo-heavy-industries-additional-notes-page-1.png](https://d3epheqghktydj.cloudfront.net/extend-ai-sumitomo-heavy-industries-additional-notes-page-1.png) *Image: extend-ai-sumitomo-heavy-industries-additional-notes-page-1.png* **Output:** ![extend-ai-hierarchy-extracted-notes-page.png](https://d3epheqghktydj.cloudfront.net/extend-ai-hierarchy-extracted-notes-page.png) *Image: extend-ai-hierarchy-extracted-notes-page.png* **Input:** ![landing-ai-scanned-two-column-text-study-area.png](https://d3epheqghktydj.cloudfront.net/landing-ai-scanned-two-column-text-study-area.png) *Image: landing-ai-scanned-two-column-text-study-area.png* **Output:** ![extend-ai-parsed-study-area-section.png](https://d3epheqghktydj.cloudfront.net/extend-ai-parsed-study-area-section.png) *Image: extend-ai-parsed-study-area-section.png* **Bottom line:** If your top priority is getting readable markdown with section hierarchy preserved across mixed PDFs, this was one of Extend AI's strongest behaviors in the test. ### Visual Element Retention and Captioning **Verdict:** Extend AI preserved charts and logos as structured figure blocks with descriptions, but usually translated visuals into text instead of keeping the original visual form inline. Retains charts and other non-text visuals by converting them into figure-style elements with extracted labels, values, and generated captions. This was tested on a waterfall chart, a scanned bar chart, annual-report charts, a research chart, and a logo element. **Input:** ![extend-ai-sg-and-a-rate-waterfall-chart.png](https://d3epheqghktydj.cloudfront.net/extend-ai-sg-and-a-rate-waterfall-chart.png) *Image: extend-ai-sg-and-a-rate-waterfall-chart.png* **Output:** ![extend-ai-sg-and-a-waterfall-extracted-text.png](https://d3epheqghktydj.cloudfront.net/extend-ai-sg-and-a-waterfall-extracted-text.png) *Image: extend-ai-sg-and-a-waterfall-extracted-text.png* **Input:** ![landing-ai-tree-mortality-by-year-and-cut-bar-chart-1.png](https://d3epheqghktydj.cloudfront.net/landing-ai-tree-mortality-by-year-and-cut-bar-chart-1.png) *Image: landing-ai-tree-mortality-by-year-and-cut-bar-chart-1.png* **Output:** ![extend-ai-parsed-chart-tree-cutting-methods.png](https://d3epheqghktydj.cloudfront.net/extend-ai-parsed-chart-tree-cutting-methods.png) *Image: extend-ai-parsed-chart-tree-cutting-methods.png* **Input:** ![hybrid_earningspdf_target_logo.png](https://d3epheqghktydj.cloudfront.net/hybrid_earningspdf_target_logo.png) *Image: hybrid_earningspdf_target_logo.png* **Output:** ![hybrid_earningspdf_parsed_logo.png](https://d3epheqghktydj.cloudfront.net/hybrid_earningspdf_parsed_logo.png) *Image: hybrid_earningspdf_parsed_logo.png* **Bottom line:** Good if you want charts and logos retained in markdown as descriptive elements; weaker if you need the original visual presentation preserved inline. ### OCR for Signatures, Stamps, and Faint Markings **Verdict:** Extend AI successfully captured low-visibility non-body-text elements that many parsers skip. Extracts non-body scanned markings beyond standard text, including signature blocks, a blurry audit-firm stamp, and faint handwritten marks from a research paper title page. **Input:** ![extend-ai-target-annual-report-signature-block.png](https://d3epheqghktydj.cloudfront.net/extend-ai-target-annual-report-signature-block.png) *Image: extend-ai-target-annual-report-signature-block.png* **Output:** ![extend-ai-parsed-signature-block-brian-c-cornell.png](https://d3epheqghktydj.cloudfront.net/extend-ai-parsed-signature-block-brian-c-cornell.png) *Image: extend-ai-parsed-signature-block-brian-c-cornell.png* **Input:** ![extend-ai-blurred-ernst-young-stamp.png](https://d3epheqghktydj.cloudfront.net/extend-ai-blurred-ernst-young-stamp.png) *Image: extend-ai-blurred-ernst-young-stamp.png* **Output:** ![extend-ai-parsed-ernst-young-stamp-page-number.png](https://d3epheqghktydj.cloudfront.net/extend-ai-parsed-ernst-young-stamp-page-number.png) *Image: extend-ai-parsed-ernst-young-stamp-page-number.png* **Input:** ![extend-ai-usda-forest-service-research-note-cover-handwritten.png](https://d3epheqghktydj.cloudfront.net/extend-ai-usda-forest-service-research-note-cover-handwritten.png) *Image: extend-ai-usda-forest-service-research-note-cover-handwritten.png* **Output:** ![extend-ai-parsed-handwriting-ocr-output.png](https://d3epheqghktydj.cloudfront.net/extend-ai-parsed-handwriting-ocr-output.png) *Image: extend-ai-parsed-handwriting-ocr-output.png* **Bottom line:** A notable strength: Extend AI kept signatures, stamps, and faint markings in the extracted output instead of silently omitting them. ### API-Based Markdown Export **Verdict:** The tested workflow was fully automated and ended in downloadable markdown output. Accepts PDF uploads, processes them automatically, and returns markdown files through a hosted API workflow. The report also shows a Developers area with API key creation, supporting programmatic use. **Input:** [File: llamaparse-hybrid-earnings-pdf-1.pdf](https://d3epheqghktydj.cloudfront.net/llamaparse-hybrid-earnings-pdf-1.pdf) **Output:** [File: extend-ai-extendai-hybrid-earnings-pdf-output-6.md](https://d3epheqghktydj.cloudfront.net/extend-ai-extendai-hybrid-earnings-pdf-output-6.md) **Input:** [File: llamaparse-sumitomo-financial-pdf-1.pdf](https://d3epheqghktydj.cloudfront.net/llamaparse-sumitomo-financial-pdf-1.pdf) **Output:** [File: extend-ai-extendai-financialpdf-output-5.md](https://d3epheqghktydj.cloudfront.net/extend-ai-extendai-financialpdf-output-5.md) **Input:** ``` Need to create credentials for programmatic API use. ``` **Output:** ![extend-ai-extendai-developers-api-keys-empty-state.png](https://d3epheqghktydj.cloudfront.net/extend-ai-extendai-developers-api-keys-empty-state.png) *Image: extend-ai-extendai-developers-api-keys-empty-state.png* **Bottom line:** The report supports Extend AI as a real hosted API workflow: upload PDF, process automatically, and retrieve markdown output. ## Pricing | Plan | Price | Notes | | --- | --- | --- | | Pay As You Go | Free to start | Includes 10,000 free credits, then usage-based pricing. Access to all APIs, Studio, OCR, workflows, and evaluation tools. | | Scale | $500/month | Includes 50,000 credits per month, higher rate limits, volume discounts, Slack support, and compliance options. | | Enterprise | Custom pricing | Includes self-hosted deployment, SSO/SAML, RBAC, custom models, dedicated support, and enterprise agreements. | ## Is It Right For You? **Use it if** - You need to extract nested metadata, summaries, and row arrays from invoices or bank statements into JSON. - You want a reviewable extraction flow with confidence metadata before export. - You can tolerate a cleanup pass for reordered sections, null transaction IDs, or label-text leakage. **Skip it if** - You need guaranteed `transaction_id` extraction on bank-statement rows. - You need the output schema order to match your input exactly. - You need broad document-type coverage beyond finance PDFs; this report only tested one bank statement and one invoice. ## Classification - **Category:** productivity - **Subcategory:** pdf-tools - **Type:** other - **Built for:** Other ## Frequently Asked Questions **Q: Which document types were tested in this report?** A bank statement PDF and an invoice PDF were tested. Both were extracted into structured JSON outputs. **Q: Did Extend AI preserve the supplied schema order?** Not always. The report says the extracted JSON reordered some top-level sections instead of matching the input schema sequence exactly. **Q: Were bank-statement transaction IDs extracted?** No. The tested bank-statement rows showed `transaction_id: null`. **Q: How accurate were the summary totals?** The invoice totals matched the source, but the bank statement summary reported `total_transactions: 49` while the reviewer expected 40 after excluding balance-forward, tax, and charge entries. **Q: Did any scalar fields include extra label text?** Yes. The invoice `payment_terms` field came back as `Payment Terms 30 Days` instead of just `30 Days`. **Q: Did the interface show confidence scores?** Yes. The invoice extraction view surfaced OCR confidence values for station, summary, advertiser, and line_items. **Q: What pricing plans were listed?** Pay As You Go is free to start with 10,000 credits, Scale is $500/month with 50,000 credits, and Enterprise is custom pricing. ## Similar Tools AI tools similar to Extend AI: - [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 ## Need a custom AI solution for this use case? If you are looking to build a custom PDF extraction, schema-driven data extraction, or financial document parsing 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).