| What it does | Manage the verified knowledge, permissions, and proof behind every AI answer.
| Open-source memory platform for AI agents
|
|---|
| Stage | Not given
| Not given
|
|---|
| Founded | Not given
| Not given
|
|---|
| Based in | Not given
| DE
|
|---|
| Pricing model | Freemium
| Not given
|
|---|
| Pricing | Starter $29/month (1 workspace, 3 team members, 3 collections, 250 documents, 1 AI Application). Pro $99/month (3 workspaces, 10 team members, 20 collections, 2,500 documents, 5 AI Applications). Team $249/month (10 workspaces, 30 team members, unlimited collections, 15,000 documents, 20 AI Applicat
| Free: $0/month with 1M tokens and 1 workspace (no card required). Standard: $1.00 per 1M tokens plus $5 per additional workspace. Enterprise: contact for pricing with bring-your-own-cloud deployment. Open-source engine available free to self-host.
|
|---|
| Key features | - Verified knowledge management with ownership, review dates, and source tracking
- Permission-based access control per AI application
- Citation-backed answers and source coverage checks
- Answer testing in Answer Playground
- Hosted documentation publishing with custom domains
- Knowledge Health scoring and monitoring
- Source change detection and monitoring
- Import and governance of existing docs and files
| - Unified vector search, knowledge graphs, and relational storage
- Automatic knowledge graph generation from data sources
- Multi-tenant support with isolated workspaces
- Data source integrations (Slack, Notion, Google Drive, GitHub, etc.)
- Self-improving memory that learns from use
- Multiple deployment options (cloud, self-hosted, air-gapped)
- Agent framework integrations (LangGraph, CrewAI, OpenAI SDK, MCP)
- Support for multiple vector and graph databases
- GDPR compliance and encryption at rest and in transit
- Built-in graph visualization of company brain
|
|---|
| What makes it different | - Separates verification and permissions from retrieval, deciding what is reviewed and safe before AI uses it
- Enables different AI applications to have different knowledge boundaries from one governed source
- Provides audit trail showing sources, verification, and permissions behind every answer
- Prevents AI hallucinations through source requirements and refusal when knowledge is missing
- Publishes documentation directly from verified sources keeping it aligned with AI knowledge
| - Combines vectors with graph relationships and generated data models for connected context retrieval
- State of the art performance on BEAM benchmark (79% vs 73.4% at 100k tokens)
- Keeps memory costs flat as data grows compared to baseline LLM approaches
- Fully open-source with no database lock-in
- Updates memory as source data changes, not just static snapshots
|
|---|
| Free plan | Not given
| Not given
|
|---|
| Open source | Not given
| Not given
|
|---|
| Platforms | Not given
| Not given
|
|---|
| Public API | Not given
| Not given
|
|---|
| Community votes | 0 | 0 |
|---|
| DR (Domain Rating by Ahrefs) | 26 ▲ +1 (up) since last check | 70 ● no change since last check |
|---|
| Trust Flow (Majestic) | 21 | 14 |
|---|
| Citation Flow (Majestic) | 19 | 43 |
|---|
| Referring domains (Majestic) | 13 | 1089 |
|---|
Wiki