Dev tools · alternatives · 2026
24 alternatives to ExtractBench, an open-source schema extraction benchmark
ExtractBench - A Benchmark for Schema-Guided Enterprise Document Extraction - run-llama/ExtractBench
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
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Documind is an open-source tool that turns documents into structured data using AI. What it does: - Extracts specific data from PDFs based on your custom schema - Returns clean, structured JSON that's ready to use - Works with just a PDF link + your schema definition Just run npm install documind to get started.
2024 · github.com · its alternatives →
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- 5KG
Hi HN! My latest side project is knowledge graph that maps the French culinary network using data extracted from restaurant reviews from LeFooding.com. The project uses LLMs to extract structured information from unstructured text. Some technical aspects you may be interested in: - Used structured generation to reliably parse unstructured text into a consistent schema - Tested multiple models (Mistral-7B-v0.3, Llama3.2-3B, gpt4o-mini) for information extraction - Created an interactive visualization using gephi-lite and Retina (WebGL) - Built (with Claude) a simple Flask web app to clean and…
2025 · theophilecantelob.re · its alternatives →
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Extract web data into structured JSON, no scraper required.
Jun 2026 · tabstack.ai · its alternatives →
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Hi HackerNews, Lately, I have seen an explosion in posts offering paid APIs/services to get unstructured data into LLMs (i.e. langchain extract, ragflow, unstructured, unstract, just to name a few) and I have been largely disappointed by them, either because they fail to implement multimodal support, fail to give good context for "really tricky" PDFs / Word docs / Powerpoints, or are just plain difficult to use. In light of all these posts I figured I'd share my solution that has been working smoothly for me and my clients. I put it up on GitHub for free so you can check it…
2024 · github.com · its alternatives →
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I recently built a small open-source tool to benchmark different LLM API endpoints — including OpenAI, Claude, and self-hosted models (like llama.cpp). It runs a configurable number of test requests and reports two key metrics: • First-token latency (ms): How long it takes for the first token to appear • Output speed (tokens/sec): Overall output fluency Demo: https://llmapitest.com/ Code: https://github.com/qjr87/llm-api-test The goal is to provide a simple, visual, and reproducible way to evaluate performance across different LLM providers, including…
2025 · llmapitest.com · its alternatives →
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ChunkHound’s goal is simple: local-first codebase intelligence that helps you pull deep, core-dev-level insights on demand, generate always-up-to-date docs, and scale from small repos to enterprise monorepos — while staying free + open source and provider-agnostic (VoyageAI / OpenAI / Qwen3, Anthropic / OpenAI / Gemini / Grok, and more). I’d love your feedback — and if you have, thank you for being part of the journey!
Jan 2026 · github.com · its alternatives →
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NinjaDoc Ai▲90Hey 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…
2025 · ninjadoc.ai · its alternatives →
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2022 · memgraph.com · its alternatives →
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A look at modern database approaches and how Citus scales PG
2016 · softwareengineeringdaily.com · its alternatives →
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Hi, I'm building an open-source self-hostable document extraction tool powered by LLM. There are popular data extraction tools and OCR tools in the market. None of them are open source. Most accounting firms, law firms, insurance, back office, and real-estate folks would like to use a tool like this. You can add PDF documents, Images, and audio files and create columns to answer questions on documents or extract information into tabular format. Access to repo: https://github.com/harishdeivanayagam/rowfill Screenshots:…
2025 · github.com · its alternatives →
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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 · its alternatives →
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When building workflows that rely on LLMs, we commonly use structured output for programmatic use cases like converting an invoice into rows or meeting transcripts into tickets or even complex PDFs into database entries. The model may return the schema you want, but with hallucinated values like `invoice_date` being off by 2 months or the transcript array ordered wrongly. The JSON is valid, but the values are not. Structured output today is a big part of using LLMs, especially when building deterministic workflows. Current structured output benchmarks (e.g., JSONSchemaBench) only validate…
Apr 2026 · interfaze.ai · its alternatives →
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Hey HN, solo dev here. After years of frustration with how LLMs handle complex documents, especially PDFs with tables, I decided to build a solution myself. My approach uses a Markdown conversion step to preserve the table structure, which seems to work surprisingly well for chunking. This little parser is the first public piece of a much larger, privacy-focused AI platform I'm building. I'm pretty much running on fumes financially, so any feedback, critique, or support is massively appreciated. Happy to answer any questions about the approach!
Nov 2025 · github.com · its alternatives →
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Build data processing and data analysis pipelines that leverage the power of LLMs 🧠 - anishathalye/semlib
2025 · github.com · its alternatives →
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LLM-Powered document extraction & analysis tool
2024 · dataku.ai · its alternatives →
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Improved file parsing for LLM’s. Contribute to Filimoa/open-parse development by creating an account on GitHub.
2024 · github.com · its alternatives →
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A framework for creating semi-automatic web content extractors - AlexMathew/scrapple
2015 · github.com · its alternatives →
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Hey! We’ve built a data extraction tool to flexibly automate data and document processing. You’ve probably seen a few of these, so have we! A few of us have been varyingly stuck trying to automate the extraction of borrower financials for the past 5 years. We think that there are a few missing features of most data extraction tools. * They are usually too complex to quickly get up and running * They are overly constrained in terms of what workflows and documents they support We’ve always felt like speed and flexibility were sticking points, so we went slightly orthogonal to the alternatives.…
2024 · go.sea.dev · its alternatives →
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2016 · siphonjs.com · its alternatives →
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A repository that contains models, datasets, and fine-tuning techniques for DB-GPT, with the purpose of enhancing model performance in Text-to-SQL - eosphoros-ai/DB-GPT-Hub
2023 · github.com · its alternatives →
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CI linter for LLM structured-output schemas
Jun 2026 · danmercede.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →