Amna Yaqoob@amnayaqoob

Industrial maintenance teams often receive disconnected sensor readings, sound anomalies and model scores without a clear explanation of what they mean or what evidence is missing. Telltale bridges that gap through an evidence-grounded maintenance decision-support workflow. The platform brings together local machine-learning services for sensor failure-risk estimation, machine-sound anomaly detection and bearing fault classification. A FastAPI backend organizes available results into assessment snapshots, preserving original scores, model provenance and data-quality limitations. A central AI analysis service uses AMD Token Factory for three interpretation tasks: AI Result Explanation, Multi-Model Analysis, and Evidence & Uncertainty Review. Structured template-based workflows support Maintenance Report Generation and Ask Telltale, providing predictable outputs grounded in available assessment data. Our separately developed frontend is being integrated with these APIs to present model indications, missing evidence and maintenance context in one technician-focused experience. Existing approved playbook guidance supports inspection recommendations where applicable. Telltale's distinction is not simply combining models: it separates prediction from explanation, keeps different score types distinct and makes uncertainty visible. Missing evidence is never treated as proof that a machine is healthy. AI-generated interpretations support human review rather than autonomous equipment control. The result is a traceable path from machine signals to maintenance understanding, helping technicians review indications, prioritize inspections and document findings without presenting model predictions as confirmed mechanical diagnoses. Technologies: Python, FastAPI, Pydantic, LightGBM, SHAP, ONNX Runtime, NumPy, pandas, SciPy, React, and AMD Token Factory API.

Hedgify is an autonomous, multi-agent portfolio insurance system built for the Alpaca AI Trading Agents Hackathon (lablab.ai). It solves a problem every equity investor knows intimately: the panic-sell. When markets crash, retail investors liquidate their holdings to stop the bleeding — crystallizing losses, triggering tax events, and inevitably missing the rebound. Hedgify replaces that reflex with insurance: instead of selling your stocks when danger approaches, the system automatically buys protective put options — capping your downside while you keep every single share and ride the recovery. The system is architected as a Supervisor–Worker multi-agent pipeline. The Monitor Agent polls live portfolio data from Alpaca's paper trading API, tracks the all-time peak value, and computes real-time drawdown the moment any poll lands. When the drawdown crosses its threshold, the Monitor persists a snapshot, fires a structured alert into the database, broadcasts it over WebSocket to any connected dashboards, and hands off to the Hedge Executor Agent. The Executor then runs its gauntlet: an idempotency guard first checks whether the symbol already carries active protection (sixteen duplicate alerts become exactly zero duplicate orders); the live kill-switch is consulted, letting an operator disable autonomous trading mid-crisis without restarting anything; then the agent queries Alpaca's live options chain over its dedicated data API, matches the target strike (5% out-of-the-money by default) to the closest actually listed contract, validates expiry against the settings table, checks the premium against the configured budget, and places a real order through Alpaca's trading API — then polls asynchronously for the actual fill price, recording genuine market premiums rather than estimates.

TripAI is an AI-powered flight and travel planning agent developed by Team Infinite Mind for the AI Factory Hackathon. It transforms fragmented travel planning into one intelligent natural-language conversation. Using LangGraph, Groq, FastAPI, Aviationstack, and Tavily, TripAI understands user travel requests, extracts requirements, retrieves relevant flight and travel information, discovers hotel options, and generates an organized AI travel plan. Its modern Next.js interface brings the complete experience together, making travel planning smarter, faster, simpler, and more convenient for users.

🌎 Hybrid Hackathon | 💻 Online Build: 3–8 November 2026 | On-site Phase: 8 November 2026 📍 On-site Venue: Pierpont Place 163 W Pierpont Ave, Salt Lake City, UT 84101, USA ✨ Please note that travel and accommodation are not covered.

🌎 Hybrid Hackathon | 💻 Online Build: 12-17 October 2026 | On-site phase: 17-18 October 2026 To participate in the hackathon, simply click Sign up with AMD. If you are not already a member of the AMD AI Developer Program (ADP), you will need to create an account. The AMD Developer Hackathon: ACT III is a hands-on event for developers, founders, engineers and builders who want to push what’s possible with AI on real infrastructure. 📍 If approved for the on-site experience, you'll also have the opportunity to showcase your project live. Travel and accommodation will not be covered.

🌎 Online Hackathon | 💻 Dates: 28 August–4 September 2026 | 🏆 $6,000 Prize Pool Build AI trading agents on Alpaca — autonomous agents and trading apps using Alpaca's Trading API, MCP server and CLI. 🌍 Fully online hackathon. Join and build from anywhere in the world.

🌎 Online Hackathon | 📅 August 3–10, 2026| 💻 Powered by native.builder The official native.builder hackathon, hosted by NativelyAI and lablab.ai. Join founders, developers, designers, and builders to create real AI-native applications powered by native.builder: from idea to deployed product, fully in the cloud. 💻 This hackathon is fully online. No travel required.