
Sports Intel AI is a cutting-edge MLB voice agent that revolutionizes sports analytics through real-time AI-powered insights. Built with Next.js frontend and FastAPI backend, it features multiple Mistral AI agents for specialized tasks including multilingual analysis, code generation, NFT metadata creation, and advanced reasoning capabilities. The platform integrates Mistral AI's powerful language models to create personalized agent configurations, enabling users to generate custom sports intelligence bots tailored to their specific teams and preferences. Key Mistral AI agents include multilingual content generation for international sports coverage, code generation for custom analytics tools, and intelligent reasoning for complex sports scenarios. Additional features include ElevenLabs voice interaction, real-time data processing, sentiment analysis, and predictive analytics for betting insights. The system combines official MLB APIs, news feeds, and social media analysis with Mistral AI's advanced capabilities to deliver comprehensive sports intelligence. Deployed on Vercel with robust backend infrastructure, Sports Intel AI represents the future of sports analytics, making complex data accessible through intuitive voice interactions and AI-powered personalized agents.
21 Sep 2025

AgentInsightX is a GPT‑5 powered platform that unifies vendor intelligence with AI workflow analytics so teams can make faster, safer decisions. Enterprises depend on dozens of external providers and increasingly complex LLM pipelines, yet visibility into performance, risk, cost, and compliance is fragmented. AgentInsightX connects to contracts, tickets, logs, model telemetry, and finance systems; builds a living knowledge graph of vendors and workflows; and continuously scores reliability, security, and ROI. The platform monitors LLM pipelines end‑to‑end—data quality, latency, cost, drift, bias, and PII exposure while tracing lineage for every prompt, model, and tool call. Policy checks and anomaly detection trigger alerts and automated actions (create a ticket, roll back a model, notify a vendor). Dashboards serve procurement, data science, and compliance with role‑based access, audit‑ready reports, and SLA tracking. A natural‑language copilot answers questions such as “Which vendor poses the highest risk this quarter?” or “Why did response quality drop last week?” AgentInsightX’s differentiators are its unified view across vendors and AI workflows, an extensible connector and metric catalog, secure private deployment, and agentic playbooks for routine governance tasks. The result: reduced risk and spend, improved model quality, and accelerated vendor and AI operations.
24 Aug 2025
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- Photogrammetry Processing: Automatically processes drone images to create orthomosaic maps. - Modern Image Alignment: Uses edge detection, feature matching, and static point analysis for precise image placement. - Interactive Map Visualization: Displays processed images as overlays on interactive maps using Folium. - Multi-Resolution Tiling: Supports efficient map rendering at multiple zoom levels. - Performance Optimizations:Utilizes parallel processing and optimized image handling for large datasets. - Customizable Overlays: Enhanced overlays with popups, markers, and custom CSS for improved user experience. ## Usage - Upload drone images via the web interface. - Start photogrammetry processing from the dashboard. - View the generated orthomosaic and overlays on the interactive map. Key Technologies - Python, Django for backend and web framework - OpenCV, NumPy, Pillow for image processing - Folium** for map visualization - Concurrent Futures for parallel processing Advanced Techniques - Edge-based and Feature-based Alignment: Ensures accurate image stitching using Canny edge detection and ORB/SIFT feature matching. - Static Point Analysis: Fine-tunes image placement by analyzing overlapping features, similar to panorama stitching. - Multi-Resolution Tiles: Generates smaller, optimized PNG overlays for efficient map loading.
15 Jun 2025

The Autonomous Space Health Guardian (ASHG) is an AI-driven system designed to monitor and optimize astronaut health during space missions. It leverages machine learning models to analyze biometric data, predict potential health risks, and provide real-time insights for preventive care. The system integrates a Flask-based API for AI-powered predictions and a Streamlit web app for an intuitive user interface. Using a combination of deep learning models and real-time monitoring, ASHG ensures astronauts receive proactive health recommendations, reducing the risk of medical emergencies in space. The AI agent can detect anomalies in vital signs, predict potential illnesses, and suggest personalized countermeasures. Additionally, it can adapt to environmental factors such as microgravity and radiation exposure, enhancing astronaut well-being. Designed for NASA, SpaceX, and deep-space exploration, this innovative system can revolutionize space health management, enabling safer and more efficient long-duration missions
9 Feb 2025
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The Daily Network Outage Forecaster: Empowering Underserved Communities During Climate Challenges Introduction Network connectivity has become an essential lifeline for education, communication, and emergency response. However, in underserved areas, where infrastructure is fragile, weather-induced network outages can have severe consequences. These disruptions exacerbate existing inequalities and significantly impact vulnerable communities, especially during emergencies. Events like the Los Angeles wildfires have shown how sudden environmental changes can sever critical communication lifelines, leaving entire communities isolated when connectivity is needed most. To address these challenges, the Daily Network Outage Forecaster offers a proactive solution. This AI-powered tool predicts potential network disruptions by analyzing real-time weather data, historical outage records, and regional infrastructure vulnerabilities. It enables schools, community centers, and local authorities to prepare effectively, ensuring systems dependent on connectivity remain operational during critical times.
26 Jan 2025

Reduced Food Costs and Dependency: By empowering individuals to grow their own food, governments can indirectly reduce the strain on food supply chains, potentially leading to lower food prices and reduced reliance on external sources. Improved Public Health: Homegrown, organic produce can contribute to healthier communities, reducing healthcare costs associated with diet-related illnesses. Community Resilience: Urban gardening can foster a sense of community, strengthen social bonds, and create more resilient neighborhoods, which can indirectly reduce the burden on government services. New Social Programs may be created to promote the planting, harvesting and communal exchange of urban food, providing access to seeds and other resources. Thus, our GRUF App shall play a very important role, leveraging the power of xAI Grok to help us advance towards a much healthier and stronger economy.
15 Dec 2024