| What it does | Open-source memory platform for AI agents
| Decision-input integrity for AI agents and oracle risk intelligence
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| Stage | Not given
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| Founded | Not given
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| Based in | DE
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| Pricing model | Not given
| Freemium
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| Pricing | 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.
| Free: 100 trial credits after email verification. Paid plans: Developer $209.92/month (2,519 USDC annually) with 60,000 credits/month; Team $1007.42/month (12,089 USDC annually) with 300,000 credits/month; Scale $3207.42/month (38,489 USDC annually) with 1,000,000 credits/month; Enterprise custom pr
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| Key features | - 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
| - Multi-source oracle price comparison across 10 providers
- Cross-chain coverage across EVM, Solana and Cosmos chains
- 15-minute price snapshots with on-demand verification
- Pre-trade assessment for proposed trades, loans, and actions
- EIP-712 signed portable proofs and attestations
- Position stress testing against protocol thresholds
- Oracle Watch monitoring for changing conditions
- REST API, AI/MCP, and Guard SDK integration paths
- Batch query priority queue for teams and high-volume applications
- 90-day historical snapshots and reliability rankings
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| What makes it different | - 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
| - Evidence that travels with the decision through signed portable proofs
- Explainable assessments showing oracle source, agreement, and freshness before execution
- Pay only for evidence your system actually uses via per-call credit metering
- One credit wallet across all endpoints without feature gates
- Machine-native x402 protocol for autonomous agents to discover and pay per check
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| Free plan | Not given
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| Open source | Not given
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| Platforms | Not given
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| Public API | Not given
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 70 ● no change since last check | 4 ▲ +1 (up) since last check |
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| Trust Flow (Majestic) | 14 | 2 |
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| Citation Flow (Majestic) | 43 | 25 |
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| Referring domains (Majestic) | 1089 | 22 |
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Insight