# Memora: AI-Powered Organizational Memory & Enterprise Knowledge Graph

> Memora is an enterprise AI knowledge management platform that unifies scattered organizational knowledge across Slack, GitHub, Jira, Confluence, Google Drive, and meetings into a searchable, living organizational memory powered by Graph RAG (Retrieval-Augmented Generation).

> Full documentation, glossary, and complete 100+ article catalog: https://memora.company/llms-full.txt

## Core Product Pillars & Architecture

- [Graph RAG Architecture](https://memora.company/glossary/graph-rag): Knowledge retrieval combining graph topology with dense vector embeddings to eliminate hallucinations.
- [Organizational Memory Engine](https://memora.company/glossary/ai-memory-fundamental): Persistent enterprise memory that captures facts, decisions, and architectural context as work happens.
- [AST Code Intelligence](https://memora.company/blog/ast-code-intelligence-graph-rag): Polyglot Tree-sitter parsing and call-graph traversal delivering surgical codebase context.
- [Model Context Protocol (MCP)](https://memora.company/mcp): Open standard stdio/SSE connectors feeding verified memory directly to Claude Code, Cursor, and Windsurf.
- [Zero-Leakage RBAC](https://memora.company/blog/can-enterprise-ai-search-respect-access-controls-rbac): Cryptographic query-time access control ensuring strict document-level security.

## Interactive Tools & Calculators

- [Context Window Token Calculator](https://memora.company/tools/context-window-token-calculator): Calculate token waste from file stuffing vs Graph RAG subgraphs across Claude and GPT-4o.
- [Engineering Knowledge Risk Calculator](https://memora.company/tools/engineering-knowledge-risk): Estimate dollar risk of undocumented architecture and tribal knowledge silos.
- [Interactive Company Memory Demo](https://memora.company/demo/ask-company-memory): Live sandbox query interface across mock Slack, GitHub, Jira, and Google Meet datasets.
- [Vector RAG vs Graph RAG Architecture Evaluator](https://memora.company/tools/rag-vs-graphrag-evaluator): Evaluate dense vector embeddings vs knowledge graph topology fit.
- [Enterprise Knowledge Loss Calculator](https://memora.company/tools/knowledge-loss-calculator): Measure financial impact of developer onboarding drag and search overhead.

## Flagship Architecture Guides

- [13 RAG Chunking Strategies vs Graph RAG](https://memora.company/blog/13-rag-chunking-strategies-vs-graph-rag): Technical breakdown of 13 chunking methods and why Graph RAG solves the chunk boundary problem.
- [Agentic Coding Toward Autonomous Engineering](https://memora.company/blog/agentic-coding-toward-autonomous-engineering): Moving from Copilot autocomplete to multi-file autonomous agents with AST graphs and ADRs.
- [Indexed vs Federated vs MCP Enterprise Search](https://memora.company/blog/indexed-vs-federated-vs-mcp-enterprise-search): Complete architectural comparison of data pipeline connectors vs local MCP stdio servers.
- [What Is AI Memory? Enterprise Architecture Guide](https://memora.company/blog/what-is-ai-memory-enterprise-guide): Working, episodic, semantic, and long-term memory hierarchy for AI agents.
- [What is an MCP Server? Complete Setup Guide](https://memora.company/blog/what-is-an-mcp-server-complete-guide): Protocol specification, JSON-RPC 2.0 primitives, and setup for Cursor and Claude Desktop.
- [Enterprise Search vs Conversational AI](https://memora.company/blog/enterprise-search-vs-conversational-ai-comparison): Why standard chatbots hallucinate on company policies and how Graph RAG delivers verified search.
- [Context Distillation in AI](https://memora.company/blog/context-distillation-vs-ai-organizational-memory): LLM prompt compression, attention caching, and why organizational memory slashes token costs.
- [Best MCP Servers for Developers in 2026](https://memora.company/blog/best-mcp-servers-for-developers-2026): Top Model Context Protocol servers for daily developer velocity, debugging, and code intelligence.

## Enterprise Comparisons & Buyer Guides

- [Best AI Agent Software for Enterprise Search (2026)](https://memora.company/blog/best-ai-agent-software-for-enterprise-search-2026): Objective 7-tool comparison: Memora, Glean, GoSearch, Moveworks, Kore.ai, Coveo, and Guru.
- [Top 7 Glean Alternatives for Enterprise AI Search](https://memora.company/blog/top-glean-alternatives-enterprise-ai-search): Evaluation of enterprise search platforms for technical and engineering teams.
- [Memora vs GoSearch](https://memora.company/blog/memora-vs-gosearch): Flat document link indexing compared against living Graph RAG organizational memory and AST code search.
- [Memora vs Moveworks](https://memora.company/blog/memora-vs-moveworks): IT help desk ticket deflection compared against developer-first organizational memory.

## Sitemaps & Machine-Readable Catalogs

- [Sitemap Index](https://memora.company/sitemap.xml): XML sitemap index for search engines.
- [Blog Sitemap](https://memora.company/blog-sitemap.xml): Dedicated sitemap for all research articles.
- [Full LLM Manifest](https://memora.company/llms-full.txt): Complete catalog of all 100+ articles, use-cases, and glossary terms.