Cyberette Is Building Forensic-Grade AI for a Post-Truth Internet

Why It Matters

By turning deepfake detection into actionable forensic evidence, Cyberette helps law‑enforcement, banks, and enterprises mitigate financial loss and personal harm, filling a gap left by generic authenticity tools.

Key Takeaways

• 99.7% detection accuracy across tested datasets
• Real‑time analysis under two seconds
• Provides provenance, model, and IP indicators
• Deployable on‑premise or cloud, GPU/CPU optimized
• Targets fraud, sextortion, and high‑risk investigations

Pulse Analysis

The rise of AI‑generated media has turned deepfakes from a novelty into a weapon for fraud, sextortion, and political manipulation. While many services simply label content as “real” or “fake,” investigators require granular evidence that can hold up in court or internal audits. Cyberette’s forensics‑first approach answers that demand by dissecting how a file was altered, identifying the likely generative model, and exposing manipulation timestamps. This level of detail transforms a binary verdict into a forensic trail, enabling law‑enforcement, banks, and media organisations to trace the origin of synthetic attacks.

Technically, Cyberette combines landmark‑based geometry checks, heat‑map anomaly scoring, and sentiment analysis to spot inconsistencies in seconds. Its lightweight models achieve 99.7 % accuracy on benchmark datasets while maintaining sub‑two‑second latency, even on standard CPUs. The platform embeds C2PA provenance tags and watermark verification, delivering tamper‑evident metadata that aligns with industry standards from Microsoft and Adobe. APIs can run in the cloud or on‑premise, allowing high‑security environments to keep data behind firewalls without sacrificing performance, a crucial factor for defence and financial institutions.

Backed by Rabobank, a Microsoft grant, and university research, Cyberette has already secured pilots with Dutch and Singaporean government agencies, a Colombian forensic team, and several banks. Its focus on high‑impact cases—such as kidnapping threats, sextortion, and large‑scale fraud—positions the startup to capture a niche market that generic deep‑fake detectors overlook. As synthetic media quality improves and platform incentives lag, demand for real‑time, explainable forensics is set to surge, making Cyberette’s upcoming seed round and product rollout a bellwether for the next wave of media integrity solutions.