Engram provides a persistent memory layer for AI agents, storing complete conversation transcripts verbatim so users can search and recall anything across ChatGPT, Claude, Cursor, or any MCP-compatible tool. The platform automatically redacts secrets and PII from stored memory, with an optional zero-knowledge vault for intentionally keeping encrypted credentials. Built on Cloudflare Workers with sub-50ms global latency, Engram enables organizations to maintain context continuity across all their AI interactions.
- Artificial Intelligence
- AI Agents
- Developer Tools
- Software Only
Funding
Funding not disclosed
Founders
Product
Problem
AI assistants and agents currently operate with short-lived context windows that lose previous conversations, forcing users to repeat information or rely on memory products that compress and summarize data. This fragmentation means context established in one AI tool doesn't carry over to another, and lossy summarization destroys the detail and nuance needed for complex workflows.
Solution
Engram provides a universal memory layer that stores complete, verbatim transcripts of AI conversations — never summarized or compressed — so users can recall anything across ChatGPT, Claude, Cursor, or any MCP-compatible agent. The platform automatically detects and redacts API keys, tokens, and PII before storage, keeping memory clean while preserving full context. Built on the Model Context Protocol, Engram connects to any MCP-compatible agent in minutes, with semantic vector search enabling instant retrieval across thousands of conversations. The zero-knowledge vault encrypts secrets AES-256-GCM on the user's device before upload, ensuring the server never accesses sensitive values.
Target Audience
Primary users are AI developers, enterprises, and power users who work across multiple AI assistants and need persistent, searchable conversation history with strong security and compliance controls.
Features
- Verbatim storage of complete conversation transcripts with no lossy summarization
- Semantic vector search with automatic edge embedding for instant retrieval across all conversations
- Native Model Context Protocol (MCP) support for connecting Claude, GPT, and custom agents
- Edge-first architecture powered by Cloudflare Workers, D1, and Vectorize with sub-50ms global latency
- Multi-tenant organization isolation with API keys, tenant scoping, and audit trails
- Automatic detection and redaction of credentials, tokens, and PII from stored memory
- Zero-knowledge vault with AES-256-GCM client-side encryption for intentional secret storage
- Tool call tracking that stores invocations alongside messages for workflow replay and debugging