Ontomics: Extracting knowledge from code to optimize LLMs

Ontomics: Knowledge Extraction for LLM Optimization

Ontomics is a powerful tool designed to extract structured domain knowledge directly from your codebases. This extracted knowledge is then used to significantly optimize the performance of Large Language Models (LLMs) and reduce the time spent on agentic search. By transforming code into a knowledge graph, Ontomics provides a more efficient way for LLMs to access and utilize information, leading to reduced token consumption and faster response times.

What Ontomics Does

Ontomics analyzes your source code to identify and represent key entities, relationships, and concepts within your project. It builds a knowledge graph that captures the underlying domain logic and structure embedded in your code. This graph serves as a highly efficient and condensed representation of your codebase's knowledge, which can then be queried by LLMs. The primary benefit is a drastic reduction in the amount of text (tokens) an LLM needs to process to understand your project's domain, thereby lowering computational costs and improving inference speed.

Key Features

• Codebase Analysis: Parses various programming languages to extract semantic information.
• Knowledge Graph Generation: Creates a structured, queryable graph representation of domain knowledge.
• LLM Token Reduction: Enables LLMs to access knowledge without processing the entire codebase, saving tokens.
• Agentic Search Optimization: Speeds up agentic search by providing direct access to relevant domain concepts.
• Open Source: Available on GitHub for integration and customization.

Who Ontomics Is For

Ontomics is an essential tool for AI builders , software engineers , and MLOps professionals working with LLMs. If you are developing AI agents that need to understand and interact with complex codebases, or if you are looking to reduce the operational costs associated with LLM deployments, Ontomics offers a direct solution. Developers building custom LLM applications, fine-tuning models on proprietary code, or integrating LLMs into existing software architectures will find Ontomics invaluable for enhancing efficiency and performance.