🦉 Data Versioning and ML Experiments
Refine high-quality datasets and visual AI models
Neo4j graph construction from unstructured data using LLMs
A system for agentic LLM-powered data processing and ETL
Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
The Context Layer for unstructured data: typed, versioned datasets over S3, GCS, Azure
Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc.
🔮 Instill Core is a full-stack AI infrastructure tool for data, model and pipeline orchestration, designed to streamline every aspect of building versatile AI-first applications
An on-premises, OCR-free unstructured data extraction, markdown conversion and benchmarking toolkit. (https://idp-leaderboard.org/)
Nomic Developer API SDK
ContextGem: Effortless LLM extraction from documents
Fast and efficient unstructured data extraction. Written in Rust with bindings for many languages.
A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting the requirements of high concurrency and ultra-low latency.
Optimized LLM-Powered Data Processing: up to 1000x speedups with fast, accurate query processing, that's as simple as writing Pandas code
Get clean data from tricky documents, powered by vision-language models ⚡
A curated list of resources for Document Understanding (DU) topic
visual data prep powered by python
The open document intelligence platform for builders and hackers - DMS for the agentic world
Interactively explore unstructured datasets from your dataframe.
Curate better data for LLMs
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