Provared vs Demi
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Provared compared with Demi
| Detail | 
Provared | 
Demi |
|---|
| What it does | Proof of what an AI agent was allowed to do, and what it then did
| The AI assistant who gets work done, before it slips
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| Stage | Startup
| Not given
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| Founded | 2026
| Not given
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| Based in | Not given
| Not given
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| Pricing model | Open source
| Freemium
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| Pricing | Not given
| Free plan with up to $50 in free credits; Individual plan $25/month including 5,000 credits per month; Team plan with custom pricing.
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| Key features | - Signed permissions with passkey authentication
- Receipts for each agent action with signatures
- Free checker tool to verify compliance
- Quantum-safe signatures (Ed25519 and ML-DSA-87)
- Permission narrowing for helper agents
- Permission cancellation with signed acknowledgement
- JavaScript and Python libraries
- LangChain and Pydantic AI middleware
| - Drafts email replies in your voice
- Prepares meeting briefs automatically
- Captures and tracks commitments
- Updates CRM automatically
- Connects to 100+ tools including Gmail, Slack, and HubSpot
- Learns work patterns without workflow setup
- Morning and evening digests of what needs attention
- Surfaces forgotten follow-ups and open loops
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| What makes it different | - Only open-source project combining machine-checkable limits, permission narrowing for helpers, and signed permission cancellation
- Built entirely from published standards with no hand-made components
- Free and no dependencies, sends nothing anywhere or holds money
- Distinguishes between record integrity and whether agent stayed within permission
- All published versions stay available for backward compatibility
| - Proactive: surfaces work that needs attention before you ask, rather than waiting for you to prompt
- No setup required: builds workflows automatically from your patterns, not from a configuration wizard
- Full control: everything external or consequential waits for your approval before sending or changing systems
- Multi-tool context: learns across all your tools to understand your tone, priorities, and patterns
- Privacy-first: data encrypted end-to-end, SOC 2 Type II compliant, and never used to train models
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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 | 32 ▼ −1 (down) since last check |
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| Trust Flow (Majestic) | 0 | 6 |
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| Citation Flow (Majestic) | 0 | 32 |
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| Referring domains (Majestic) | 0 | 144 |
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4 details filled in for both companies.
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