Democratising Generative AI 
Transforming Enterprises with AI Solutions at Scale
Multi-format Input
Process documents, audio, weblinks, and more
Structured Data Extraction
Extract actionable data on the go
RAG-optimized Chunking
Optimized for Retrieval Augmented Generation
OmniParse is your all-in-one solution for converting diverse data formats into structured, actionable information. Whether it's documents, audio, or web content.
What we offer
Advanced Data Transformation
Leverage AI-driven techniques to cleanse, structure, and enrich your raw data, ensuring high-quality datasets ready for machine learning applications.
State-of-the-Art Model Training
Utilize cutting-edge methods like transfer learning and neural architecture search to train accurate and efficient models tailored to your needs.
Comprehensive AI Evaluations
Ensure the reliability of your AI models with rigorous testing, including stress tests, bias detection, and performance benchmarks.
Products
OmniParse
Convert Anything into Structured Actionable Data
Multi-format input support
AI-powered data extraction
Customizable output structures
Real-time processing
RAG SaaS
Deploy Agentic RAG Solutions at Scale to your Enterprise
Agentic AI is generatingScrapio
Get Structured Data from the Web at Scale
(Coming Soon)
just now
Blogs
Introducing OmniParse
OmniParse is a platform that ingests and parses any unstructured data into structured, actionable data optimized for GenAI (LLM) applications. Whether you are working with documents, tables, images, videos, audio files, or web pages, OmniParse prepares your data to be clean, structured, and ready for AI applications such as RAG, fine-tuning, and more
Read More →Introducing AI Engineering Academy
AI-related careers are becoming increasingly sought-after. However, the abundance of learning resources scattered across the internet can lead to confusion about where to start. AI Engineering Academy aims to provide a structured learning path to help you learn Applied GenAI effectively.
Read More →Introducing Indic LLM leaderboard
Recent advancements in Indic Large Language Models (LLMs) underscore progress, yet the absence of a unified evaluation framework complicates tracking and comparison. This challenge exacerbates existing issues like data scarcity and inadequate language tools. A unified evaluation framework with benchmarks is crucial to overcome these challenges and drive meaningful advancement in the field.
Read More →Introducing Ambari
In this blog, I am thrilled to share insights into the meticulous approach we undertook to train Amabri Base Cognitive-Lab/Ambari-7B-Instruct-v0.1 and Amabri Instruct Cognitive-Lab/Ambari-7B-Instruct-v0.1. Offering a high-level glimpse into our process, this narrative serves as a precursor to the forthcoming revelation of all technical details— the culmination of extensive testing and evaluation. Stay tuned as we unravel the intricacies that led to the creation of Amabri, an innovative open-source bilingual Kannada-English Large Language Model.
Read More →
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