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Extrai

An open-source tool to fight LLM randomness in data extraction

Details

External ID
45803134
Source
HN
Company
—
Product
Extrai
Website domain
github.com
Launched
Nov. 3, 2025
Cohort
—
Upvotes
5
Upvotes percentile
0.0982532751091703
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

A few months ago I was working on a flight search engine that would include pet transport costs (I know a few by hearth but storing them and make the calculations in the UI would be nice) While I was collecting pet pricing from several airlines I strugled to extract data in a common format without hallucinated values.That's when I thought: What if I use multiple LLMs and take the most common response to improve accuracy?This idea became this new project. You provide your documents, an SQLModel schema, an LLM provider, plus what you'd like to extract and Extrai does the rest. Including storing them in a DB afterwards.There are a few other features such as SQLModel generation based on your documents, hierarchical extraction to manage nested objects more efficiently and built-in analytics.Feedback is more than welcomed, since it's still a work in progress!I built a landing page for people interested in a managed solution (I also had fun with threeJS!)Let me know what you thinkLanding page: extrai.xyz Github: https://github.com/Telsho/Extrai

Enrichment

Theme
browser automation and scraping for AI
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
AI feature
Project type
Hobby / open-source project
Normalized one-liner
open-source tool to reduce randomness in llm data extraction
Manually corrected
False

Could you build this?

Yes This is a lightweight open-source tool wrapping LLM structured outputs (e.g., JSON schema enforcement and validation retries) to normalize extracted flight and pricing data.

Discussion

No comments on this launch.

Competitors

Other products that read as similar to this one — 97 launches clear the similarity bar, closest 8 shown.

Attention rank: #96 of 98 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 3 days after the earliest competitor.

Other launches for this product

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