Data as of Aug 16, 2026 · Based on 1,172 AI responses · See how Parse measures this
AI Document Data Extraction Software
ParseChatGPT + Google AIParse
https://parse.gl
Measured across ChatGPT & Google AI| # | Brand | What AI says | Mention rate |
|---|---|---|---|
| 1 |  Alphabet | 57% | |
| 2 |  Microsoft | 48% | |
| 3 |  Amazon | 44% | |
| 4 |  NanonetsA fast-rising solution, recognized for AI-powered invoice automation and custom model training. | A fast-rising solution, recognized for AI-powered invoice automation and custom model training. | 35% |
| 5 |  DocparserConsistently recommended for rule-based table extraction and no-code business automation workflows. | Consistently recommended for rule-based table extraction and no-code business automation workflows. | 33% |
| 6 |  RossumFrequently mentioned for its AI that processes invoices without requiring predefined templates. | Frequently mentioned for its AI that processes invoices without requiring predefined templates. | 27% |
| 7 |  AbbyyA long-standing enterprise solution, frequently cited for high-accuracy invoice and document processing. | A long-standing enterprise solution, frequently cited for high-accuracy invoice and document processing. | 26% |
| 8 |  Parseur | 23% | |
| 9 |  TabulaA popular open-source tool recommended for extracting simple tables from digital PDFs. | A popular open-source tool recommended for extracting simple tables from digital PDFs. | 17% |
| 10 |  DocsumoA notable new entrant specializing in structured data extraction from financial documents. | A notable new entrant specializing in structured data extraction from financial documents. | 16% |
| 11 |  Reducto | 14% | |
| 12 |  camelot-py | 14% | |
| 13 |  Adobe | 13% | |
| 14 |  LlamaIndex | 13% | |
| 15 |  Parsio | 13% | |
| 16 |  Mindee | 12% | |
| 17 |  Tesseract OCR | 12% | |
| 18 |  Veryfi | 11% | |
| 19 |  Airparser | 11% | |
| 20 |  Klippa | 10% | |
| 21 |  Unstructured | 9% | |
| 22 |  DocuClipper | 9% | |
| 23 |  Energent AI | 9% | |
| 24 |  AlgoDocs | 8% | |
| 25 | PDFPlumber | 7% |
Who wins on each AI
The same market, seen by two models.
Sources AI cited
reddit.com is the page AI reaches for most here, cited in 50% of analyzed answers.
Jumped from rank #30 to #7 between October and March.
“A legacy enterprise OCR tool” → “A modern intelligent document processing (IDP) platform”
Rose from rank #8 in October to #1 by March across the niche.
| Brand | ChatGPT Search | Google AI Mode | Comparison |
|---|---|---|---|
 Google Cloud Document AI | 78% | 65% | |
 Amazon Textract | 78% | 38% | |
 Azure AI Document Intelligence | 72% | 49% | |
| LlamaParse | 36% | 42% | |
| Rossum | 51% | 42% |
The two models disagree most about Abbyy (ChatGPT #7, Google #22) and LlamaIndex (ChatGPT #18, Google #7).
Google now leads the AI document extraction space, representative of a broader shift where major cloud platforms are increasingly displacing specialized tools. This consolidation is most visible in general-purpose queries, while dedicated invoice processing remains a more fragmented and competitive field.
Across 1,172 AI responses, Alphabet is mentioned most, named in 57% of them, followed by Microsoft (48%) and Amazon (44%).
Parse measures each brand's mention rate — the share of answers naming it — across 1,172 AI responses to this market's buyer questions. Answers are collected daily and the ranking is published weekly.
Brands enter the ranking when AI answers mention them. Parse collects answers daily and publishes the re-measured set weekly, so new brands appear as AI starts recommending them.
GoogleMicrosoftAmazonInitial responses in November recommended a mix of specialized tools like
Initial responses in November recommended a mix of specialized tools like
GoogleAmazonMicrosoftEarly answers in October 2025 offered a wide variety of lesser-known, specialized services like 
Amazon Textract
Kudrawhich AI document extraction services can i use?
Early answers in October 2025 offered a wide variety of lesser-known, specialized services like
