Natanael Sijabat@naellabit68927

ZippoAI Live Intelligence Agent is a local-first AI platform that combines Bright Data's live web intelligence with persistent AI memory to deliver real-time business insights. Traditional AI assistants often rely on static knowledge and cannot accurately answer questions about recent market changes, competitor activity, regulatory updates, or emerging risks. ZippoAI solves this by combining live public web data with an intelligent memory layer. When a user submits a research query, ZippoAI first checks its local PostgreSQL cache and Qdrant semantic memory to reuse previously collected intelligence. If the information is missing or outdated, the platform automatically retrieves fresh public web data through Bright Data SERP APIs. This approach reduces costs, improves response times, and minimizes unnecessary external requests. The retrieved data is analyzed by an AI reasoning engine and transformed into structured intelligence reports containing executive summaries, key signals, recommendations, confidence indicators, and source references. Instead of manually reviewing dozens of websites, users receive concise, actionable insights that support faster decision-making. ZippoAI is designed for competitor monitoring, market research, go-to-market intelligence, compliance awareness, supplier assessment, and strategic planning. Every research result can be stored in memory, creating a continuously growing knowledge base that becomes more valuable over time. A dedicated Live Research interface allows users to investigate companies, competitors, industries, and market events using both historical knowledge and live web intelligence. This combination of memory, reasoning, and real-time data provides a unique advantage over traditional AI assistants.

ReguAI is an intelligent incident response and compliance workflow platform that automates the entire incident management lifecycle. When production incidents occur, engineering teams face critical challenges: responding quickly while maintaining comprehensive documentation for compliance, audits, and post-mortem analysis. ReguAI solves this by transforming raw incident data into comprehensive, audit-ready documentation instantly. The platform features intelligent rule-based AI report generation that automatically creates multi-section incident reports including risk classification, timeline reconstruction, compliance checklists, technical action plans, stakeholder summaries, and detailed post-mortem analysis. A real-time dashboard monitors all incidents with live metrics showing total incidents, active cases, resolution times, and severity breakdowns. Automated workflow management creates and tracks incident response tasks with priority levels, ownership assignment, and status tracking. Every action is automatically logged with timestamps, actors, and state changes in compliance-ready audit trails that satisfy SOC2, ISO 27001, and other regulatory requirements. The platform exports incidents as formatted Markdown post-mortems ready for stakeholder review. Smart template selection based on incident type (Security, Payment, API Contract, General) ensures relevant, context-aware report generation. Built on Next.js, React, TypeScript, PostgreSQL with Prisma ORM, and containerized with Docker, ReguAI uses a deterministic rule-based AI approach ensuring zero latency, 100% reliability, cost efficiency, offline capability, and fully explainable audit compliance. Perfect for startups needing compliance documentation, scale-ups managing growing incident volumes, and enterprises requiring audit-ready incident management.

Our project is an AI-powered Smart Product Assistant designed to help users discover, understand, and compare products more easily through natural language interaction. The system allows users to ask questions about products, get intelligent recommendations, compare specifications, and receive helpful explanations based on product data. The main goal of this project is to create a practical AI assistant that can improve the product exploration experience, especially for users who need fast, clear, and personalized information before making a decision. Based on the PRD, this project includes several key components: a backend API, AI model integration, product data management, user interaction flow, and a frontend interface that connects directly with the AI assistant. The backend is designed to handle requests, manage product-related data, connect with the AI model, and return accurate responses to the user. The AI system has also been connected to Ollama 3 running on AMD Developer Cloud, allowing the assistant to process user prompts and generate relevant responses. This setup demonstrates how AMD cloud infrastructure can be used to run AI workloads and support real-world application development. This project was fully designed and developed by two Senior Fullstack Engineers, Agung Laksono and Naila Sijabat. We worked on the system from end to end, including backend architecture, API development, frontend integration, AI connection, database preparation, and deployment setup. We are submitting this project to Lablab AI as a completed solution that demonstrates our ability to build an AI-powered product assistant with practical use cases, scalable architecture, and real implementation using modern AI technology.

📅 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.

🌍 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.

📅 May 11–19, 2026 • May 11 – 19: Online Build Phase. • May 18 (Hybrid Build Day – Online & Onsite) • May 19 (Demos & Awards – Online & Onsite) 🌍 Hybrid event. Join online from anywhere or build onsite at the venue. 🏆 Winners will be announced live on stage at the AI & Big Data Expo North America on May 19 📍 On-site Venue (May 18–19): San Jose McEnery Convention Center, CA, USA 🤝 Join solo or with a team. 🎟 FREE AI & Big Data Expo North America ticket included for participants that are able to join the on-site phase. 🏆Compete for a $10,000 prize pool 🧑‍💻 Apply now to design, prototype, and showcase enterprise-ready innovation.