Long-term memory for AI agents that organizes itself and corrects itself
Stage
Not given
MVP
Founded
Not given
Not given
Based in
US
SE
Pricing model
Freemium
Free
Pricing
Free plan at $0 USD; Pro plan at $5 USD per month.
Personal: Free during early access. Unlimited memories, all agents with separate memories, no card required. Enterprise: On request, set up by the team for departmental organization with cross-department sharing and direct support.
Key features
Entity-graph spreading activation for cross-vocabulary retrieval
Works with any LLM model
No LLM or GPU in retrieval path
Point-in-time and windowed recall
Timestamped memories
Fixed recall cost as memory grows
Self-correcting memory that updates when facts change
Historical memory queries with time-based retrieval
Automatic topic organization and hierarchy
Separate memory for each agent with controlled sharing
Multi-agent support via MCP, REST API, or LangGraph
AES-256 encryption at rest and in backups
OAuth 2.1 authentication and API key management
Data export and deletion capabilities
37 MCP tools with automated verification on every code change
What makes it different
Reaches answers across unrelated documents that share no keywords, where vector search scores zero
Deterministic retrieval with no model in the path, so results never vary between queries
Constant per-query cost regardless of memory size, even at 32,000 words
No infrastructure to run—no vector database, cluster, or GPU needed
Works with any model, so small local models gain the most from better retrieval
Understands what changed, when it was true, and where it belongs - beyond vector database similarity
Never contradicts itself by automatically replacing outdated facts
Fully GDPR aligned with built-in privacy by design
Two-minute integration with Claude, ChatGPT, Cursor and any MCP client
Data stays in Europe on AWS eu-north-1 and never used for model training