NinjaDoc Ai
Hey HN, I'm the founder of Ninjadoc AI. I've spent years working with document processing, and I've always been frustrated by the existing solutions for structured data extraction. The core problem is that most tools force you into one of two bad options: Template-based extractors: You define fixed regions or rules. These are incredibly brittle and break the moment a document layout changes slightly (e.g., a new invoice template from a vendor). ML-based extractors: These require you to gather hundreds (sometimes thousands) of your own labeled documents to train a custom model for each…
NinjaDoc Ai launched on August 26, 2025 with 90 votes, #408 of 8,530 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 1 year on.
What it does
Ninjadoc AI gives you structured data you can actually trust. Create schemas by asking your documents simple questions 💬 Our API returns JSON with the exact coordinates for every single piece of data. Get undeniable proof of where the information came from.
Extract document answers with bounding boxes, citation URLs, and MCP-ready outputs. Give your agents source-grounded evidence for 250 free credits monthly.
Get structured PDF answers with bounding boxes, citation URLs, and MCP-ready outputs for auditable agent workflows. Get structured answers from PDFs with bounding boxes, citation URLs, and MCP-ready outputs, so every AI answer can be traced to the source. Ask questions in plain English. Get structured answers with page, bbox, and source evidence attached. Most tools return extracted text. Ninjadoc returns answers with the source evidence an agent or reviewer needs to verify them. 250 credits per dollar. Credits never expire. Start with what you need, scale as you grow. When AI makes a decision based on a document, you need more than an answer. You need proof. Ninjadoc returns exact source…from ninjadoc.ai
In the maker’s words, at launch
Hey HN, I'm the founder of Ninjadoc AI. I've spent years working with document processing, and I've always been frustrated by the existing solutions for structured data extraction. The core problem is that most tools force you into one of two bad options: Template-based extractors: You define fixed regions or rules.…
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