| What it does | Identify people by how they move using biomechanical AI, even when faces aren't visible
| AI security for chatbots, RAG systems, and agentic workflows
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| Stage | Not given
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| Based in | IL
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| Pricing model | Not given
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| Key features | - Identify known people from video galleries or watchlists
- Determine if two videos show the same person
- Re-identify people within and across videos
- Works with low-resolution video and long distances
- Functions despite occlusions, masks and appearance changes
- Analyzes ground camera video feeds
- Does not rely on facial recognition
- Standalone deployment, integration, or OEM embedding options
| - Intent envelope specification with open JSON Schema
- Multi-turn jailbreak and injection testing across web, mobile, and voice
- Deterministic execution boundary enforcing tool allowlists
- Human-in-the-loop escalation for high-impact actions
- Identity and credential separation per agent
- Supervisor check for independent action validation
- Free AI attack surface assessment tool
- Findings mapped to OWASP, MITRE ATLAS, and NIST AI RMF
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| What makes it different | - Based on 20+ years of biomechanics research from Ben-Gurion University
- Requires only a few usable walking steps to create a biomechanical signature
- Works without facial recognition where other systems struggle
- Founded by researchers with 20+ years biomechanics expertise and successful startup founders
| - Open-source intent envelope specification implementable with own engineers
- Calibrated defenses from red team findings rather than off-the-shelf policies
- Findings carried through to runtime controls and access changes, not just reports
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 10 ▲ +3 (up) since last check | 1 ▲ +1 (up) since last check |
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| Trust Flow (Majestic) | 6 | 0 |
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| Citation Flow (Majestic) | 7 | 12 |
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| Referring domains (Majestic) | 21 | 1 |
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MotionAnalytics
SecuredAI