Endgame vs Exabase
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Endgame compared with Exabase
| Detail | 
Endgame | 
Exabase |
|---|
| What it does | Context graph for AI-native revenue teams
| Context infrastructure for AI agents
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|---|
| Stage | Established
| Startup
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| Founded | 2021
| Not given
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| Based in | Not given
| GB
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| Pricing model | Contact for pricing
| Freemium
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| Pricing | Not given
| Not given
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| Key features | - 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
| - Memory system with self-managing advanced memory
- Isolated per-tenant instances with version rollback
- Portable context server with files, notes and links
- Sub-document multi-modal hybrid search
- Structured data extraction from PDFs, websites and images
- Autonomous agents for knowledge base automation
- 99.9% uptime SLA
- AES-256 encryption at rest and SSL in transit
- TypeScript SDK and REST API
- Model-agnostic and framework-agnostic
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| What makes it different | - 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
| - Cut token spend by up to 81% through persistent agent memory instead of full context window stuffing
- State-of-the-art on two leading AI memory benchmarks
- Full-stack data layer eliminating need for multiple services
- Production-tested at scale powering Fabric platform
- Self-improving memory that tracks relationships and resolves contradictions
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| Free plan | Not given
| Not given
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| Open source | Not given
| Not given
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| Platforms | Not given
| Not given
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| Public API | Not given
| Not given
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 48 ▼ −2 (down) since last check | 29 ● no change since last check |
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| Trust Flow (Majestic) | 8 | 11 |
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| Citation Flow (Majestic) | 35 | 32 |
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| Referring domains (Majestic) | 323 | 122 |
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5 details filled in for both companies.
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