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🤓 Latest Submissions
AEGIS - AI Firewall for LLM Protection
Every company deploying AI agents faces the same invisible threat: prompt injection. Traditional WAFs detect SQL injection and XSS, but LLM attacks are plain English — no signatures to match. AEGIS WAF solves this with 5 independent defense layers running in parallel: Pattern Detection catches known attack signatures in ~2ms, Intent Analysis uses LLM-powered classification to understand malicious intent, Semantic Guard matches against known attack vectors, Context Tracking monitors multi-turn session behavior, and Output Guard scans LLM responses for data leaks and policy violations before they reach the user. The platform includes a real-time security dashboard, interactive demo where users can test attacks live, Slack integration for instant threat alerts, complete audit logging, and configurable security policies. Built with Next.js 15, TypeScript, and deployed on Vercel, AEGIS integrates into any LLM application in just 3 lines of code. Named after the shield of Zeus in Greek mythology, AEGIS provides divine protection for AI — making agents safe to deploy on the public internet.
7 Feb 2026
EngineIQ - Democratizing Knowledge Access
EngineIQ addresses the £100B global knowledge inequality crisis affecting 50 million technology workers. Engineers waste 10+ hours weekly searching scattered information across Slack, GitHub, wikis, and documents. Offshore teams struggle with time zones. New hires take 12 weeks to become productive. Contractors face access barriers. Our solution: An autonomous AI agent built with Google Gemini 2.0 and Qdrant vector search that provides 24/7 semantic search across all five modalities - text, code, images, videos, and audio. The system features an 8-node LangGraph agent workflow with permission-aware filtering and real-time indexing (~12 seconds from upload to searchable). Real impact across four continents: Anh in Vietnam resolves production MongoDB crises at 3 AM without waking the US team. Carlos in Mexico gets transparent contractor access to architecture documentation. Fatima in Dubai learns Kubernetes through visual content despite language barriers. Priya in India onboards in 3 weeks instead of 12 weeks. Quantified business value: £1.26M annual productivity value for 50-person teams, 70% reduction in search time, 50% faster onboarding, 3x team velocity increase, and burnout reduction from 52% to ~18%. Market opportunity: £5.2B TAM (Enterprise Search), £850M SAM (AI-powered search), £42M SOM (500 target companies). Revenue model: £999-£2,999/month SaaS with 10x LTV/CAC ratio. Technology: 1,200+ documents indexed, multimodal fusion with Gemini 2.0 Flash Exp, hybrid semantic search with Qdrant, production-ready architecture deployed on Railway with 99.9% uptime. Live demo and open-source repository available. Built for AI Genesis Hackathon - demonstrating best use of Google Gemini (all 5 modalities) and Qdrant (hybrid search with 4-collection architecture). For every engineer experiencing knowledge inequality - we're building equity in technology, one search at a time.
19 Nov 2025
