what document parsing api should a non technical founder pick if we need to extract data from old pdfs
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
what document parsing api should a non technical founder pick if we need to extract data from old pdfs
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
ChatGPT real searches (2)
Classes come from the query-classifier (a local Laya model). 2 of 2 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT2 real searches · gpt-6
best document parsing APIs OCR PDF extraction 2026 LLM structured data old scanned PDFs pricing ease of use Google ↗
Google Document AI Azure AI Document Intelligence AWS Textract Unstructured LlamaParse API comparison scanned PDFs tables handwriting 2026 Google ↗
- 9 Best Document Parsing APIs in 2026 · extend.ai
- Best Document Extraction APIs (PDF to JSON) · capyparse.com
- Best Document Parsing APIs to Try in 2026 · firecrawl.dev
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
best document parsing APIs OCR PDF extraction 2026 LLM structured data old scanned PDFs pricing ease of use OBSERVED | Google ↗ AI Mode ↗ | — | Comparison | — | — | 1x of 1 | |
Google Document AI Azure AI Document Intelligence AWS Textract Unstructured LlamaParse API comparison scanned PDFs tables handwriting 2026 OBSERVED | Google ↗ AI Mode ↗ | — | Comparison | — | — | 1x of 1 |