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ParseHawk

100% Local Document AI with API, CLI, and Web UI

Details

External ID
48671675
Source
HN
Company
—
Product
ParseHawk
Website domain
github.com
Launched
June 25, 2026
Cohort
—
Upvotes
9
Upvotes percentile
0.5484972677595629
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

I just released ParseHawk v0.1.0: Apache-2.0 licensed 100% local document AI platform that extracts JSON from PDFs, images etc. It builds on top of NuMind's NuExtract3 but additionally enforces a provided JSON schema with constrained decoding. It works on Apple Silicon with pre-bundled vllm-metal as well as Linux + NVIDIA with vllm. Looking forward to your feedback!

Enrichment

Theme
browser automation and scraping for AI
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
local document processing with api
Manually corrected
False

Could you build this?

Partial Creating a CLI and web UI for document AI is easy, but bundling and optimizing local vision-language model inference on Apple Silicon (vllm-metal) with strict schema-constrained grammar decoding requires low-level ML systems engineering.

What it would actually take: The platform requires local VLM inference (NuExtract/Qwen-VL) served via llama.cpp or vLLM Metal bindings, paired with grammar-constrained decoding engines (such as Outlines or XGrammar) to enforce JSON schemas. The hard parts are optimizing inference memory on consumer unified memory, integrating robust PDF-to-image rasterization, and ensuring constrained decoding does not crash or stall model inference.

Discussion

4 comments analyzed.

Feature requests: Windows support

Competitors

Other products that read as similar to this one — 27 launches clear the similarity bar, closest 8 shown.

Attention rank: #14 of 28 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 229 days after the earliest competitor.

Other launches for this product

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