Jin Chun Tan@tanjinchun

Keiretsu Radar is an AI-powered supplier intelligence platform that helps companies detect supplier and vendor risks earlier by turning live public web data into structured business intelligence. Inspired by the Japanese concept of keiretsu, where companies operate through deeply connected supplier and partner networks, the product treats supplier risk as a network problem rather than a single company problem. Users can enter a company, industry or supplier list and Keiretsu Radar scans public web signals such as news, company websites, hiring activity, leadership changes, regulatory updates, product availability, pricing movement and reputation signals. The system then generates a supplier network graph, risk scores, evidence cards and a boardroom ready executive brief. Bright Data acts as the primary live web intelligence layer, helping the agent collect and structure public web data reliably. The platform also includes fallback connectors for demo resilience, such as Firecrawl, Tavily, Exa, GDELT, NewsAPI and seeded demo data when live credentials are unavailable. The interface clearly labels whether it is running in Live Mode or Demo Mode. Keiretsu Radar is built for procurement, finance, strategy and risk teams that need faster supplier due diligence and earlier warning signs before disruptions appear in internal systems. Instead of manually checking scattered web pages, teams get one clear dashboard showing which suppliers are stable, which require monitoring and which present urgent risks.

KintsugiOps AI is an agentic AI platform that helps software teams identify and repair software waste before it turns into unnecessary cloud cost, slower performance and higher digital carbon impact. Inspired by the Japanese art of kintsugi, where broken pottery is repaired with gold instead of being discarded, the product applies the same idea to software systems where inefficient systems should be improved, not simply replaced. The platform uses multiple AI agents to analyse software and cloud workflows. One agent finds issues such as bloated Docker images, unused dependencies, repeated AI API calls, idle cloud resources and slow CI/CD pipelines. Another agent estimates the financial and carbon impact, while other agents recommend repairs, check risk levels and generate a clear impact report. The goal is to give engineering, DevOps and sustainability teams a simple way to understand where waste exists, what should be fixed first and how much value can be recovered. KintsugiOps AI turns messy software systems into cleaner, more efficient and more sustainable digital infrastructure.

KintsugiGuard AI is an enterprise AI governance and software repair platform that helps teams make autonomous AI workflows safer, cleaner and more accountable. As companies adopt AI agents for engineering, DevOps and cloud operations, they face two problems at once: software waste accumulates silently, while agentic actions can happen without enough oversight. KintsugiGuard AI solves this through a governed multi agent workflow. It detects issues such as bloated containers, idle cloud resources, repeated API calls, slow CI/CD pipelines and risky repair actions. The platform then estimates cost impact, carbon impact, risk level and business value before recommending what should happen next. Each repair is classified as auto approved, human review required, blocked by policy or safe to simulate only. The system also includes security inspection, governance policy checks, Gemini ready reasoning, X402 style governed payment simulation and an audit trail for every decision. The result is a practical enterprise tool that turns software waste and agentic risk into measurable, policy approved repair.

FlowFix is an AI-powered debugging assistant that helps developers understand broken engineering workflows faster. Instead of manually reading messy logs, scripts, configuration files and documentation, users can paste a failed log and related repository context such as a Dockerfile, shell script, requirements file or project notes. FlowFix then analyzes the failure and generates a structured debugging report. The tool produces a plain English error summary, explains what the workflow is trying to do, ranks likely root causes with confidence levels and supporting evidence, and creates a step-by-step fix runbook with verification commands. It also generates prevention tips and a downloadable DEBUG_RUNBOOK.md file that can be reused as team documentation. FlowFix is useful because developers often lose time not from writing code, but from figuring out why a build, setup or deployment broke. By converting scattered debugging information into an actionable runbook, FlowFix helps junior developers onboard faster, reduces debugging friction and turns one time fixes into reusable knowledge.

EchoLens is an AI powered immersive memory experience generator that transforms ordinary digital messages into interactive, shareable moments. Instead of sending a plain text message, static photo or generic greeting card, users can upload a photo, write a short message or provide a voice note. EchoLens then uses an agentic AI workflow to understand the user’s intent, emotional tone and context before generating a polished message, visual direction, scene concept and interactive web-based memory card. The project is designed around a simple idea: digital communication should feel more human. EchoLens allows users to create small immersive experiences for birthdays, appreciation notes, travel memories, event invitations, personal milestones or long distance messages. The final output can be explored as a lightweight 3D scene or animated digital card and shared through a link or QR code. For the AMD Developer Hackathon, EchoLens demonstrates how AMD Developer Cloud and ROCm can support practical AI inference for creative, multimodal and agentic applications. The system combines AI agents, multimodal input and immersive web technology to create a complete end-to-end experience from raw user input to a finished interactive memory.

📅 June 12–19, 2026 • June 12: Kick-off Stream • June 12–19: Online Build Phase • June 19: Project Submissions Ends 🌍 Fully online hackathon. Join and build from anywhere in the world. 🤝 Build practical enterprise workflows where AI agents communicate, coordinate, exchange context, and complete work together. 🧠 Powered by Band and Codeband, built for collaborative AI systems and agent orchestration. 🏆 Prize Pool: $10,000+ 🧑‍💻 Apply now to build the next generation of enterprise multi-agent systems.

🌉 On-site Only Hackathon | 📅 June 27–28, 2026 | 📍 San Francisco, CA This is an in-person hackathon in San Francisco for selected participants. Capacity is limited to 150 people, teams must include 3–5 members, and there is no online or hybrid participation. Build and optimize real-time AI applications that run directly on Snapdragon-powered mobile devices using ExecuTorch. 📍 On-site Venue (June 27–28): The Web Data Loft 625 2nd St, San Francisco, CA 📱 Build on Samsung Galaxy S25 Ultra devices powered by Snapdragon 🧠 Learn from Qualcomm and Meta experts through workshops, mentorship, and hands-on support 🏆 Prizes include Meta Quest 3 headsets, Ray-Ban Meta AI Glasses, and post-event project support 🧑‍💻 Apply now to build the future of on-device AI with ExecuTorch and Snapdragon. Once pre-approved, you will receive further instructions on how to complete the acceptance process. Application deadline: June 15, 2026.

Grab your ideas, spin up compute, and start building what’s next! Start with $100 in AMD Developer Cloud credits and begin building right away. Get access to hands-on tutorials, workshops, and curated learning resources to help you build faster and go further. To unlock credits and join the hackathon, sign up for the AMD AI Developer Program. 💰 $10,000 total prize pool Developers, builders, and innovators - bring your boldest ideas and let’s turn them into real AI systems on AMD.

🌍 Hybrid Hackathon | 💻 Online Build: May 25–30,2026 | 📍 SF Onsite Finale: May 30–31,2026 We’ve unlocked the web for your AI. Now build what wasn’t possible before. Build AI agents with live web data, then join the SF onsite finale at Bright Data’s new Web Data Loft. 🚀 The onsite experience will take place during the opening of Bright Data’s new SF space, The Web Data Loft. 📍 On-site Venue (May 30–31): The Web Data Loft 625 2nd St, San Francisco, CA 🏆 $18,300 cash prize + Bright Data AI Startup Program opportunities 🍕 Free food, drinks, networking, workshops, mentorship, and live demos 🎁 Onsite attendees are automatically entered into a live giveaway for 4 × $100 Amazon gift cards. 🧑‍💻 Apply now to build AI agents powered by real-time web access.

Build solutions that improve how software is built. Work with an AI that understands your codebase, helping you reduce repetitive work and build with real context. ⏳ Build your project in 48 hours. 🚀 Get hands-on with IBM Bob and explore how AI fits into real development workflows before it becomes standard. 💡 Build tools and workflows that developers would actually use. ⭐ Learn directly from experts throughout the event. 🤝 Join a team or build solo. 💰 Prize pool: $10,000 🧑🏻‍💻 Register before the Kick-Off Stream and start building with Bob.

⏱️ Build the next generation of Autonomous Agents in the heart of Europe’s AI Revolution. 📅 May 13 – 20, 2026 May 13 – 19: Online Build Phase. May 19: An exclusive on-site build day at Milan AI Week for selected participants. May 20: Awards Ceremony. 📍On-site Venue (May 19–20): Fiera Milano (Rho), Milan, Italy 🤝 Join solo or with a team. 🎟 FREE Milan AI Week conference ticket included for participants. 💰 $32,000+ prize pool 🧑‍💻 Apply now to turn your autonomous agent into a market-ready enterprise solution.