🤓 Latest Submissions
Aloqa: AI Receptionist for Small Business
Aloqa is an AI receptionist for small businesses in Uzbekistan and Central Asia — cafes, shops, salons — that have no CRM and no support team. Customers write in Telegram, often as voice notes, and leave reviews on maps; owners miss complaints and lose customers. Aloqa collects incoming messages, transcribes voice notes, classifies intent, urgency and risk, drafts polite replies in Russian or Uzbek, and creates actionable tasks. The owner always approves every reply — human-in-the-loop, no biometrics, no emotion detection. Built entirely in native.builder, on a mobile phone. The AI layer runs live on Fireworks AI via Edge Functions, with a deterministic rule-based fallback, so the product never fails. Security audit completed: JWT verification, restricted CORS, input validation, legacy code removed. Speechmatics, AI/ML API, Featherless AI and Bright Data are wired as integration-ready stubs. Impact: 2–3 hours of daily message handling reduced to 20–30 minutes; fewer lost customers; consistent brand voice in two languages.
10 Aug 2026
ScamShield — Fraud Detection API
ScamShield is a fraud detection REST API built for the AMD Developer Hackathon: ACT II. It analyzes text, URLs, documents, and images for phishing, social engineering, and tampering using a hybrid AI router that balances cost, speed, and accuracy. The system runs entirely on AMD infrastructure. LLM inference is routed through Fireworks AI on AMD Instinct GPUs — DeepSeek V4 Flash for text analysis and Minimax M3 for vision analysis — with a free local Ollama fallback (Gemma 4 12B) for offline use. The entire codebase is built around Google Gemma 4 31B IT as the primary model; the router always attempts Gemma first and falls back automatically when access isn't available on the current API tier, requiring zero code changes once that access is granted. Beyond AI-based analysis, ScamShield includes a 9-probe forensics engine that runs entirely offline: LSB steganography detection, histogram analysis, appended-data detection, file entropy scoring, Word VBA macro extraction, PDF JavaScript scanning, threat-keyword matching, EXIF metadata checks, and file signature verification. This engine is adapted from a production Telegram bot already used in real classrooms for cybersecurity education. A Levenshtein-based typosquatting engine specifically protects users of Central Asian banks — Kapitalbank, Click, Payme, Uzcard, and Humo — catching lookalike domains like kap1talbank.uz that standard blacklists miss. The entire project was rebuilt from an earlier multi-agent prototype into a clean, dependency-free FastAPI service, fully containerized and published publicly on GitHub Container Registry — reviewers can pull and run it with a single Docker command, no source build required. Team: NYX Sec — Jasur Mahkamov, Fergana Valley, Uzbekistan.
13 Jul 2026
ScamShield - Multi-Agent Fraud Detection
Central Asia—particularly Uzb—has seen an unprecedented surge in financial fraud, phishing, and social engineering through messaging apps like Telegram and WhatsApp. Scammers use localized social engineering in Uz and Rus, craft typo-squatted domains mimicking real banks and distribute manipulated transaction screenshots or malware-laced files. Ordinary citizens have no automated way to verify suspicious content in real time. ScamShield is a distributed, multi-agent fraud detection system built on the Band SDK. Instead of relying on one general-purpose model, four specialized agents collaborate inside a Band chat room: - ScamShield Coordinator receives the user's request, delegates sub-tasks to the right specialist agents, and synthesizes their findings into a final structured verdict (risk level, fraud probability, plain-language explanation). - Vision Agent inspects images and screenshots for editing artifacts, mismatched fonts, forged bank templates, and visual manipulation. - Stego Agent runs a production-grade forensics engine performing nine concurrent checks: LSB steganography detection, histogram analysis, appended-data detection, entropy scoring, Word macro extraction, PDF JS detection, archive scanning, CTF-flag extraction, and threat-keyword matching. - Text Agent analyzes message text and URLs for phishing patterns, urgency tactics, punycode attacks, and typo-squatting against known Uzbek bank domains. Agents are registered as independent Remote Agents on Band and communicate inside a shared Chat Room. The Coordinator reasons over incoming messages with a local LLM , decides which specialist(s) to delegate to, and the corresponding agent(s) respond inside the same room — real agent-to-agent collaboration, not a single hidden function call. In live testing, a phishing message referencing "kap1talbank.uz" was correctly flagged: CRITICAL risk, 98% fraud probability, with a clear explanation of the typo-squatting domain and social-engineering tactics used.
19 Jun 2026
