| What it does | Deepfake Detection Backed by Forensic Evidence
| Independent verification for bug fixes in C, C++ and firmware
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| Stage | Startup
| MVP
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| Founded | 2024
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| Based in | NL
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| Pricing model | Contact for pricing
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| Pricing | Not given
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| Key features | - Multi-layer forensic analysis examining visual inconsistencies, facial behaviour, audio anomalies, metadata, and traces of AI generation
- Facial movement and expression analysis to identify signs of manipulation
- Suspicious region pinpointing with visual indicators in images, videos and audio
- Metadata and provenance inspection to identify inconsistencies
- Explainable results and forensic reports for decision-making and legal proceedings
- Flexible deployment options including cloud, on-premises, containerised and air-gapped setups
- API and SDK integration into existing systems
- Landmarking analysis detecting inconsistencies in facial features and face-to-background alignment
- Behavioral signal analysis tracking blinking, breathing and emotional cues to confirm liveness
- Cross-modality checks aligning and comparing audio and video streams to expose manipulation
| - Reproduces bugs deterministically on base version before applying fix
- Verifies fix removal confirms bug returns
- Scans diffs for masking patterns like disabled sanitizers and weakened tests
- Runs on real hardware via STM32 NUCLEO boards and ST-Link
- Integrates with AI coding agents as MCP tool
- Posts verdicts as GitHub pull request comments
- Provides per-test verdicts: FIXED, BROKEN, FLAKY ON THE BENCH, FLAKY WORSE
- Runs entirely on your machines with no cloud dependency
- Generates reports for change records and regulatory compliance
- Runs builds and tests in Linux container on your machine
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| What makes it different | - Forensic evidence-backed results with explainable indicators instead of guesswork
- Research-grade technology backed by Rabobank and showcased at major tech events
- Supports investigation, intelligence, law enforcement and legal workflows with evidence-ready outputs
- Multimodal detection across video, audio, image and text with unmatched precision
| - Only verification tool that reverses the fix to prove tests actually catch the bug
- Deterministic verdict with no AI language model in decision logic
- Tests on real hardware boards, not just laptops
- Detects masking techniques that hide bugs while passing tests
- Validated public benchmark showing 4 VERIFIED and 6 REJECTED on real open-source bugs
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 6 ▲ +1 (up) since last check | 3 ▼ −1 (down) since last check |
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| Trust Flow (Majestic) | 4 | 0 |
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| Citation Flow (Majestic) | 8 | 0 |
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| Referring domains (Majestic) | 30 | 0 |
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Cyberette
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