🤝 Top Collaborators
.png&w=640&q=75)
.png&w=640&q=75)
🤓 Latest Submissions
CodeMentor
Code Mentor is a cloud-native DevSecOps environment that acts as an automated security architect sitting inside your IDE. As AI code assistants like Copilot ship code faster than ever, they're also shipping vulnerabilities at record speed — and traditional SAST/DAST tools are too slow and too noisy for developers to act on. Code Mentor solves this with four core capabilities: 🔍 Real-Time AI Scanning — Powered by Gemini 2.5 Pro on Google Vertex AI, the scanner performs context-aware semantic analysis on your code, flagging structural vulnerabilities like SQL injection, hardcoded secrets, and insecure patterns the moment you open a file. 🧠 Triple-Tier Explainability — Every vulnerability is explained three ways: an Analogy for quick intuition, a Technical deep-dive for senior engineers, and a Meme for culture-driven retention. This is the first security tool designed for how developers actually think. ⚡ 1-Click Live Fix — Unlike legacy scanners that stop at alerts, Code Mentor finishes the job. It rewrites your vulnerable code with a single click using the suggestedPatch from the AI response, then logs the fix to an audit trail for compliance reporting. 🏛️ Enterprise Policy Governance — A built-in Policy Studio enforces HIPAA, GDPR, and SOC2 compliance standards, giving enterprise teams real visibility into what policies are being violated across their codebase. The architecture runs on Next.js 14 with a Monaco Editor frontend, backed by serverless Next.js API routes deployed on Google Cloud Run via a multi-stage Alpine Linux Docker build — cutting cold starts by ~80%. The backend communicates with Vertex AI over IAM-governed service accounts, with zero user code cached or persisted, making it stateless and breach-resistant by design. A Vulnerability Sandbox ships with three pre-loaded production-flawed blueprints (auth-service.ts, query-engine.ts, env-config.yaml) so judges can experience the full scan-explain-fix pipeline instantly, with zero setup.
19 May 2026
CancerLens AI
CancerLens AI is an advanced oncological triage platform built for the AMD Developer Hackathon 2026. The platform uses a 3-agent AI pipeline running on AMD MI300X GPUs with 192GB of HBM3 memory to detect, classify, and stage cancer from medical imaging scans. Agent 1 — Extractor: Qwen2-VL running at full precision on AMD MI300X analyzes the uploaded scan and extracts detailed visual observations. Agent 2 — Analyst: Gemini 2.0 Flash cross-references imaging findings with patient context and blood report values to generate a structured clinical report including cancer type, TNM staging, and risk scoring. Agent 3 — Validator: An independent AI pass audits the report for logical consistency and assigns a reliability score before the result reaches the user. The platform was tested on real clinical teaching cases — correctly identifying Stage III Osteosarcoma from a knee X-ray, cross-referencing elevated ALP and LDH from a blood report, and detecting Glioblastoma from a brain MRI with 9-10 out of 10 reliability scores. Features include stage-specific survival statistics pulled dynamically for any cancer type, a nearest oncologist finder via Google Maps, direct links to cancer specialist hospitals, and a context-aware AI health assistant chatbot. CancerLens AI makes radiologist-level cancer detection accessible to anyone, anywhere — in seconds, not weeks. Built by Team Noxis.
10 May 2026
