Manifold vs Elpis
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Manifold compared with Elpis
| Detail | 
Manifold | 
Elpis |
|---|
| What it does | Enterprise agent platform for life sciences that enables governed data sharing and self-serve access across organizational boundaries
| Portable context for terminal coding agents
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| Stage | Not given
| Not given
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| Founded | Not given
| Not given
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| Based in | US
| Not given
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| Pricing model | Contact for pricing
| Open source
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| Pricing | Not given
| Not given
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| Key features | - Specialist agents ready to deploy for cohort building, guided analysis, and access provisioning
- Build and deploy custom agents connected to data, tools, and domain-specific workflows
- Data harmonization across molecular, clinical, imaging, and real-world data
- Role-based access control with audit trails for compliance
- Bring-your-own-cloud deployment keeps data in customer's AWS environment
- Partners access data through natural language queries without data movement
- Support for Python, R, and Nextflow analysis tools
- HIPAA, IRB, and BAA ready architecture
- SOC 2, GDPR, TX-RAMP, and NIST SP 800-171 compliance
| - Context Ledger for curating admitted instructions, files and memory
- Deterministic context admission before model processing
- Workflows with Mother agent team design and checking
- Love Spot drawing board with Matilda companion
- Desktop app with theme customization
- Support for GPT, Claude and Gemini models
- Terminal and desktop app sharing state
- Portable context for terminal coding agents
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| What makes it different | - Partners get self-serve answers in minutes instead of weeks of manual data coordination
- Data stays in your cloud while agents deliver answers across organizational boundaries
- Governance and compliance built into every agent action, not added afterward
- Go live from deal signing to active data access in days instead of months
- Embedded bioinformatics reduces time to customer insights from weeks to the same day
| - Deterministic context admission ensures agents see processed context before model receives it
- Context Ledger provides transparent curation of agent inputs
- Mother agent orchestrates multi-agent workflows with checking and merged results
- Collaborative drawing interface with AI companion
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 45 ● no change since last check | 7 ● no change since last check |
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| Trust Flow (Majestic) | 20 | 0 |
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| Citation Flow (Majestic) | 36 | 12 |
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| Referring domains (Majestic) | 218 | 6 |
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4 details filled in for both companies.
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