Alternatives
Products that do what Tabstack Structured Extraction does
Extract web data into structured JSON, no scraper required.
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2017 · link.fish
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Hey HN, It will be more of a "How I released my API without managing a website, servers, users, and payments. With 0$ up-front cost" Over the past year, I have come up with a plan of how I could release my own product without having to deal with managing users and/or dealing with payment processing. It is a 3 steps procedure: 1. Make an API that solves a problem 2. Deploy it with a serverless architecture 3. Distribute through an API Marketplace That took me about 2-3 days to develop an API using Flask, deploy it via Zappa on AWS, and release through RapidAPI. Source code of API:…
2020
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2014 · github.com
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I built a CLI tool in Go that extracts structured data (JSON, CSV, Parquet) from messy PDFs and HTML pages. The core idea: LLMs are great at understanding structure but wasteful for bulk data extraction. So smelt uses a two-pass architecture: 1. A fast Go capture layer parses the document and detects table-like regions 2. Those regions (not the whole document) get sent to Claude for schema inference — column names, types, nesting 3. The Go layer then does deterministic extraction using the inferred schema This means the LLM is never in the hot path of actual data processing. It figures out…
Mar 2026 · github.com
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2019 · github.com
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2017 · page.rest
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Turn any website into a clean structured data with one api.
26d ago · schemafetch.launchreadyal.com
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Hey all, I built a quick PoC that scrapes a webpage, sends the content to Gemini Flash, and outputs a clean, structured JSON — ready for RAG workflows. In my case, I’ll use this structured data to enhance models by integrating external knowledge sources during the generation process. Curious if you think this has potential or if there are any use cases I might have missed. Happy to share more details if there's interest!
2025 · structured.pages.dev
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This library aims to be something like pandas.read_html or table_extract Rust crate, but more idiomatic for Go. htmltable enables structured data extraction from HTML tables and URLs and requires almost no external dependencies. Tested with Go 1.18.x and 1.19.x. Complex tables with row and col spans are natively supported as well.
2022 · github.com
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2018 · github.com
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Hi HN! This Christmas I made `tysm`, a rust crates which simplifies using ChatGPT with Structured Outputs. Essentially you just tell it the rust type you want the output to conform to, and it handles creating the JSON Schema, passing it to ChatGPT's chat-completions API, and deserializing the response. Structured Outputs are very useful because they guarantee that the response will conform to whatever type you expect. I'm already finding my crate very useful since I love using Structured Outputs but I hate writing JSON Schemas myself. Technical details for rust heads: To generate the JSON…
2024 · github.com
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We build LlamaExtract, a tool that allow you to automatically extract a data model from a collection of documents, and then reusing this datamodels (JSON Schema) to extract data from documents. Available as a Python library and as an API. Announcement blog: https://www.llamaindex.ai/blog/introducing-llamaextract-beta...
2024 · github.com
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https://github.com/lazywithclass/swaggins It works by looking at the request and extracting the relevant information to populate the Swagger JSON file. I've wrote it to go with contract testing (http://martinfowler.com/articles/microservice-testing/#testing-contract-introduction), but it can also work with normal HTTP based integration tests. Any suggestion / opinion is welcome.
2016
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