Transform unstructured docs to structured data
LLM-Powered document extraction & analysis tool
Transform unstructured docs to structured data launched on January 2, 2024 with 7 votes, #1,799 of 4,438 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 2 years on.
What it does
AI data intelligence blog. Benchmark analysis, pricing trends, and model comparisons with real numbers.
AI through the lens of data. Benchmarks, pricing trends, model comparisons. Let me show you something interesting in the numbers. I counted every frontier model API available today. OpenAI, Anthropic, and Google serve roughly 90% of all production frontier inference. The concentration numbers are wild. 40+ models in 90 days. The pace is absurd. Here's the full count, month by month. AI inference costs dropped 100x in 3 years. I put it all in one table and the trend line is almost vertical. Five years of counting models, tracking prices, and benchmarking everything I can get my hands on. The three things I got right, the five things I got wrong, and the one trend I still can't explain. This…from dataku.ai
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I just open sourced my document/website extractor for Vision-LLMs2024 · github.com · ▲37Hi 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…


Structured output from LLMs without reprompting2023 · automorphic.ai · ▲174Built a tool for transforming unstructured data into structured outputs using language models (with 100% adherence). If you're facing problems getting GPT to adhere to a schema (JSON, XML, etc.) or regex, need to bulk process some unstructured data, or generate synthetic data, check it out. We run our own tuned model (you can self-host if you want), so, we're able to have incredibly fine grained control over text generation. Repository: https://github.com/automorphic-ai/trex Playground: https://automorphic.ai/playground
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