Forge Orbital vs Exabase
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Forge Orbital compared with Exabase
| Detail | 
Forge Orbital | 
Exabase |
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| What it does | AI accountability that grows into governance
| Context infrastructure for AI agents
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| Stage | Not given
| Startup
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| Founded | Not given
| Not given
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| Based in | US
| GB
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| Pricing model | Not given
| Freemium
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| Pricing | Not given
| Not given
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| Key features | - Governance: checks proposed AI actions against defined rules before execution
- Recorded decision records that can be reviewed, replayed and verified later
- Evaluation: compares AI agent performance using representative test cases and expected outcomes
- Optimization: recommends model and cache candidates based on usage, prices and evaluation evidence
- Regress detection identifies changed action paths and quality regressions
- On-premises and private cloud deployment
- Integration with existing AI tools via connectors and wrappers
- No model training on customer data; separate data boundaries from external AI providers
- Cost comparison and optimization across model and cache configurations
| - 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 | - Independent accountability: checks run inside your systems, not asking another AI to audit AI
- Your people keep authority: Forge produces decision evidence, your business enforces results
- Recorded decision evidence that auditors and regulators can examine
- Designed for consequential work in regulated industries like financial services
- Not another dashboard: integrates into your workflow without replacing your AI tools
| - 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
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| Open source | Not given
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| Platforms | 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) | Not checked yet ● no change since last check | 29 ● no change since last check |
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| Trust Flow (Majestic) | 0 | 11 |
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| Citation Flow (Majestic) | 7 | 32 |
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| Referring domains (Majestic) | 22 | 122 |
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4 details filled in for both companies.
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