Kernel Memory is an open-source reference architecture developed by Microsoft to help developers build memory systems for AI applications powered by large language models. The project focuses on enabling applications to store, index, and retrieve information so that AI systems can incorporate external knowledge when generating responses. It supports scenarios such as document ingestion, semantic search, and retrieval-augmented generation, allowing language models to answer questions using contextual information from private or enterprise datasets. Kernel Memory can ingest documents in multiple formats, process them into embeddings, and store them in searchable indexes. Applications can then query these indexed data sources to retrieve relevant information and include it as context for AI responses.

Features

  • Document ingestion and indexing for AI knowledge bases
  • Retrieval-augmented generation support for language models
  • Semantic search across structured and unstructured data
  • Embedding generation and vector storage integration
  • Architecture templates for enterprise AI memory systems
  • Integration with AI orchestration frameworks and APIs

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License

MIT License

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Additional Project Details

Programming Language

C#

Related Categories

C# Large Language Models (LLM), C# Semantic Search Tool

Registered

2026-03-06