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Echo is an autonomous multi-agent financial intelligence platform built for investors and financial teams who need real-time web data to make better decisions. At its core, Echo uses Bright Data's SERP API to continuously monitor the open web — extracting news signals, hiring trends, regulatory changes, and competitive intelligence for any publicly listed company. This live web data is combined with structured financial data from Yahoo Finance and deep analysis from multiple specialized AI agents running in parallel. Echo covers all three hackathon tracks: Track 2 (Finance & Market Intelligence): Echo delivers alternative data pipelines aggregating hiring signals, earnings indicators, and competitive pricing intelligence. Its multi-source synthesis engine combines live web signals with fundamental analysis to generate structured BUY/HOLD/SELL investment signals with confidence ratings and key reasoning. Track 3 (Security & Compliance): Echo's ComplianceAlertAgent continuously monitors regulatory changes, legal risks, and ESG compliance requirements via Bright Data, delivering structured alerts with urgency ratings to risk management teams. Track 1 (GTM Intelligence): Echo's competitive signal monitoring tracks competitor moves, pricing strategies, and market positioning in real time. Key capabilities include a Portfolio Dashboard with live signal monitoring, Signal History timeline tracking how investment thesis evolves, Stakeholder Analysis mapping supply chains and peer comparisons, ESG profiling, and full PDF financial report analysis. All signals are persisted in SQLite for historical tracking. Echo is built on a four-layer architecture: Fetch → Analysis → Synthesis → Orchestration, designed to scale from single-stock analysis to continuous portfolio monitoring.

FinAgent V2 is an autonomous multi-agent investment analysis system built for VC/PE firms, fund managers, and investment analysts who need structured, deep analysis without a dedicated research team. Unlike single-model approaches, V2 deploys five specialized AI agents coordinated by an LLM-driven Orchestrator that uses function calling to dynamically plan which agents to activate based on user input and natural language intent. Three Analysis Modes: Mode A — Market Analysis: Enter a stock ticker. The Orchestrator dispatches QuantAgent, PeerAgent, and CIOAgent in parallel to deliver complete market analysis including valuation models (PE/PB/PEG/EV-EBITDA/DCF), peer comparison, technical trends, and investment verdict. Mode B — Report + Market Analysis: Upload a financial report PDF and enter a ticker. FundamentalAgent and QuantAgent run simultaneously — one reads the document using Gemini multimodal AI, one pulls live market data via yfinance. CIOAgent then cross-analyzes both outputs, surfacing divergence signals between reported fundamentals and current market performance. Mode C — AI Dialogue: Talk to the Orchestrator in natural language. It introduces itself, asks clarifying questions, confirms the analysis plan, then dispatches the right combination of agents. True conversational orchestration that adapts to user needs. Key technical features: streaming dashboard where results appear section by section as each agent completes, intelligent peer identification using sector and geography context, reflection loop where the Orchestrator synthesizes from LLM knowledge when agent data is incomplete, and optional Featherless open-source model inference. Built on: Gemini API, OpenAI function calling, React/TypeScript, Express, Vultr (Milan region), yfinance, Featherless.

FinAgent is an autonomous AI investment analysis agent built for VC/PE firms, fund managers, and analysts who need to evaluate companies quickly without a dedicated research team. The agent accepts two inputs: a financial report PDF and a stock ticker symbol. Once submitted, it automatically orchestrates a complete investment analysis workflow without human intervention. Core capabilities: Document Intelligence: Gemini's multimodal API reads annual reports and ESG documents natively, extracting key financial metrics, investment highlights, strategic risks, and ESG ratings directly from text, tables, and charts. Real-Time Market Analysis: Live stock data via yfinance including current price, 52-week range, moving averages (MA20/50/200), and technical trend signals. Valuation Models: PE, PB, PEG, EV/EBITDA, dividend model, and a real DCF calculator where users input growth rate and discount rate assumptions. Results are cross-referenced to produce an overall valuation verdict with confidence level. Peer Comparison: The agent automatically identifies 3-5 industry competitors and fetches their real-time market data for side-by-side comparison against industry and market averages. Cross Analysis: The agent synthesizes divergence signals between reported fundamentals and current stock performance, producing a one-sentence investment verdict. Enterprise Security via Lobster Trap: All LLM calls are routed through Lobster Trap, a deep prompt inspection proxy that detects prompt injection, PII exposure, and data exfiltration attempts in real time. A live security dashboard shows every AI interaction and its risk assessment. Three-tier output structure gives users a 30-second summary card for quick decisions, core analysis for standard review, and full detailed output for deep-dive research. All sections can be exported as a PDF report. Built on: Gemini API, React, TypeScript, Express, Vultr Cloud Compute, Lobster Trap (Veea).

📅 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.