Rohan Santhosh@rohansanthoshkumar20446

Financial analysts and researchers are currently drowning in a flood of unorganized financial data, ranging from quarterly earnings transcripts and SEC filings to complex investor presentations. Extracting actionable insights like key performance indicators, forward-looking risk factors, and balanced investment theses is an incredibly labor-intensive and error-prone process. Current AI tools often suffer from hallucinations and a lack of source-grounded evidence, making them unsuitable for high-stakes institutional research. EarningsPilot AMD solves this by deploying a high-performance, multi-agent pipeline designed to automate the complete research workflow. Our multi-agent architecture includes: Parser Agent: Normalizes and chunks massive, disparate document types (PDFs, CSVs, transcripts). KPI Extraction Agent: Precisely identifies and normalizes financial metrics with direct source citations. Risk Agent: Detects forward-looking risk flags and categorizes them by severity. Thesis Agent: Synthesizes balanced Bull vs. Bear cases based solely on grounded evidence. Report Agent: Synthesizes the final dashboard-ready executive memo. To meet the rigorous demands of professional finance, we leveraged the AMD Developer Cloud and the ROCm ecosystem. We fine-tuned an EarningsPilot-Qwen-7B-LoRA adapter on 15 hours of MI300X compute time to ensure high-fidelity structured JSON output. By deploying this on a ROCm-optimized vLLM stack, we achieved inference speeds that turn minutes of manual analysis into seconds of automated intelligence. Our system provides a deterministic fallback mode for reliability during public demos, while the primary AMD-backed path delivers the scale and performance institutional investors require. EarningsPilot AMD represents a shift from "chatting with PDFs" to an actual agent-driven investment research workflow, grounded in verifiable source evidence and accelerated by industry-leading AMD hardware.

ArcTask is a demo-first platform for the Agentic Economy on Arc. A user submits a goal such as competitor research, campaign planning, or a workflow brief. The coordinator agent decomposes that goal into atomic work packages, assigns each task a priority and a USDC-denominated micro-bounty, and routes it through a visible workflow: queued, in progress, submitted, verified, and paid. The core idea is that agentic systems should not hide all value transfer inside one black-box request. In ArcTask, every unit of work becomes economically legible. Worker agents generate outputs, a verifier reviews them, and only approved work can release a payout receipt into the ledger. This makes accountability, task status, and economic flow understandable in one screen. The current hackathon build is optimized for a reliable live demo. It uses Next.js, TypeScript, Tailwind, server-side AI routes, seeded demo scenarios, browser-persisted workflow state, and a payment adapter abstraction. For stage reliability, the shipped prototype settles server-side demo receipts rather than claiming live onchain settlement, but the payout layer is intentionally structured so a real Arc and Circle-backed settlement adapter can replace the mock path cleanly. ArcTask is therefore both a polished demo and a credible architecture for software-native labor markets powered by nano-payments.

📅 May 25–31, 2026 • May 25 – 30: Online Build Phase • May 30 (Hybrid Build Day – Online & Onsite) • May 31 (Demos & Awards – Online & Onsite) 🌍 Hybrid event. Join online from anywhere or build onsite in San Francisco. 🏆 Winners will be announced live during the final demo and awards session on May 31 📍 On-site Venue (May 30–31): The Web Data Loft 625 2nd St, San Francisco, CA 🤝 Join solo or build with a team. 🏆 Compete for a $5,000 cash prize + Bright Data AI Startup Program opportunities 🧑‍💻 Apply now to build AI agents and data systems powered by real-time web access.

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. 🤝 Go solo or team up — ship something real. 💰 $21,500+ total prize pool & 1 × AMD Radeon™ AI PRO R9700 GPU up for grabs. 📍 On-site Venue (May 9-10): MindsDB SF AI Collective 3154 17th St, San Francisco, California, USA 📍On-site participation is by invitation only. Travel and accommodation expenses will not be covered. 🧑‍💻 Developers, builders, and innovators - bring your boldest ideas and let’s turn them into real AI systems on AMD.

In this hybrid hackathon powered by Arc and Circle, developers will build the next generation of Agentic economic applications using Circle’s Nanopayments infrastructure with settlement on Arc in USDC. For the first time, high-frequency, usage-based transactions between users, APIs, and AI agents can operate without gas overhead eroding margin. Arc provides stablecoin-native settlement with predictable, dollar-denominated USDC fees and deterministic, sub-second finality — enabling real-time coordination and economically viable per-action pricing at scale. 📅 April 20 – 26, 2026 • Apr 20 – 25 (Online): Submit projects by Apr 25. • Apr 25 (On-site Build – SF, CA): Teams refine projects. • Apr 26 (On-site Demos & Awards – SF, CA): Live pitches & winners announced. Get guidance from Arc and Circle experts through on-site support. 📍 On-site Venue (April 25-26): MindsDB SF AI Collective 3154 17th St, San Francisco, California, USA 🤝 Go solo or team up, it's your flow. 🏆 Compete for a $15,000+ Prize Pool. 📍 Please note: 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. 🧑🏻‍💻 Secure your spot now – sign up before the Kick-Off Stream!