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Project Raze: Neural Decontamination Platform
Project Raze — Real-Time Neural Decontamination for Enterprise AI. When sensitive data like API keys, PII, proprietary code, or copyrighted text gets baked into an LLM's training weights, there's no clean way to remove it. Full retraining costs millions and takes months. Prompt filters are a bandaid, easily bypassed. This leaves companies exposed under regulations like GDPR's "Right to be Forgotten," a request that's trivial for a database but long considered nearly impossible for a neural network. Project Raze solves this with machine unlearning, a mathematical scalpel that surgically removes specific memorized data from a model's weights while preserving 99.8% of its general intelligence. No retraining. No compromises. How it works: a four-stage pipeline first maps which weights encode the target data (Dynamic Cartography), then reverses their optimization through Adversarial Gradient Ascent. The process is stabilized with Differential Privacy noise injection to prevent catastrophic forgetting, and utility retention is continuously validated through perplexity drift monitoring. Verification matters just as much as the surgery. Every operation is stress-tested by an automated red-team agent, powered by a Gemma 2 model on Fireworks AI, that throws jailbreaks, prompt injections, and encoded extraction attacks to confirm the data is truly gone. Only then does the system issue a cryptographic SHA-256 Certificate of Erasure, logged immutably in Supabase for auditors. On the front end, a Next.js and React "Command Center" gives real-time visibility into every surgery through live telemetry, a 3D neural visualization, and before-and-after inference comparisons. Behind it, a FastAPI and PyTorch backend performs the tensor-level ablation, running up to 8x faster on AMD MI300X GPUs via ROCm. The result: a multi-million-dollar, months-long retraining crisis becomes a 12-second, auditable API call, letting enterprises comply with deletion requests on demand, with confidence.
13 Jul 2026
