| What it does | One memory, every AI tool. Write once, recall anywhere.
| Context graph for AI-native revenue teams
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| Stage | Not given
| Established
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| Founded | Not given
| 2021
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| Based in | Not given
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| Pricing model | Freemium
| Contact for pricing
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| Pricing | Free: $0 with 1,000 queries/day, 10,000 atoms, 60 req/min. Pro: $29/mo with 50,000 queries/day, 500,000 atoms, 600 req/min. Team: $149/mo with 500,000 queries/day, 5,000,000 atoms, 3,000 req/min. Enterprise: Custom limits and pricing.
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| Key features | - Persistent cross-tool memory API working with Claude, Cursor, VS Code, ChatGPT, Python, and any HTTP client
- Hebbian associations that strengthen links between concepts recalled together
- Outcome feedback that re-ranks recall based on usefulness
- Automatic query expansion along learned associations
- Python SDK with typed errors for write, read, feedback, and stats
- REST API for any HTTP client
- Per-tenant org isolation and SHA-256 hashed API keys
| - One context layer connecting all GTM tools and AI agents
- Agent observability with end-to-end tracing
- Source citations for every answer
- Permission-aware answers scoped to user access levels
- Playbook grounding to enforce business semantics
- Corrections inbox for agent-generated changes
- Integration with Claude, ChatGPT, Slack, Salesforce and other tools
- Open Model Context Protocol (MCP) for any client
- SOC 2 Type II compliance and GDPR/CCPA support
- 140x faster answers via pre-compiled context
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| What makes it different | - Learns from outcomes and improves over time, unlike vector databases that only perform similarity search
- Works across every AI tool with a single API key, not locked to one platform
- Complementary to RAG: remembers outcomes and lessons, not just document similarity
- Free tier with full API access and MCP server, no credit card required
| - 40x lower cost through pre-compiled context vs raw data processing
- 98% answer accuracy with no hallucinations through checked data
- Agent-agnostic: works with any AI tool your team uses
- Never trains on customer data with enterprise-grade security
- Set up within days with forward-deployed engineer support
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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 |
| DR (Domain Rating by Ahrefs) | 40 ▼ −1 (down) since last check | 48 ▼ −2 (down) since last check |
| Trust Flow (Majestic) | 7 | 8 |
| Citation Flow (Majestic) | 37 | 35 |
| Referring domains (Majestic) | 200 | 323 |