Krrish Yaduka@ky2803

Retail options trading is emotionally driven, highly complex, and lacks rigorous risk oversight. OptionFlow Sentinel democratizes institutional-grade quant infrastructure by providing retail traders with a fully autonomous, multi-agent AI Hedge Fund. Instead of relying on a single black-box LLM prompt, Sentinel orchestrates a highly resilient 5-agent debate graph powered by NVIDIA's Llama 3.1 70B. The process begins with the Scanner Agent, which dynamically connects to the Alpaca MCP Server to ingest real-time market news and identify volatility mispricings. The Strategy Agent then constructs complex multi-leg options profiles (such as Bear Call Spreads). Before a single dollar is risked, the Risk Officer agent strictly evaluates the proposal against the user's hard account limits, possessing absolute veto power. Finally, the Execution Agent routes approved trades into live limit orders via the Alpaca API. The architecture is built for production-grade multi-tenant security. Users link their broker accounts via a React dashboard, and the FastAPI backend securely encrypts their keys using 256-bit Fernet cryptography. Beyond live execution, Sentinel leverages the Alpaca CLI inside Celery background workers to run heavy-duty historical strategy backtests without freezing the API. Active positions are completely auto-managed. Background workers continuously poll live P&L data; if a trade hits predefined profit or loss targets, the system autonomously fires closing orders to cut human emotion entirely out of the equation. All AI reasoning, risk vetoes, and system logs are transparently streamed to the user's frontend Audit Trail.

Insight Forge is an advanced agentic validation engine designed to eliminate product risk and confirmation bias for startup founders, product managers, and investors. By automating secondary market research, the platform converts raw ideas and assumptions into verified execution blueprints. At its core, the application features an autonomous 6-step research runner that queries the web, classifies sources, extracts specific claims, maps active contradictions, and identifies knowledge gaps. Rather than just aggregating data, the platform scores evidence credibility with a custom Truth-Scoring algorithm based on source authority, date recency, and confirmation counts. To actively fight confirmation bias, a built-in adversarial Steel-Man Debate Engine simulates opposing viewpoints and presents uncertainty scores. Once research is complete, the platform generates custom validation guides containing targeted user interview scripts, survey outlines, and prototype risk matrix checklists. Teams can collaborate in real-time with heart-beat presence indicators and compare up to three projects semantically to identify shared market opportunities.

Mirror AI is an AI-powered stress testing and security evaluation platform designed to help developers build safer, more reliable AI applications. As large language models become increasingly integrated into products and workflows, ensuring their robustness against malicious inputs, hallucinations, prompt injections, and security vulnerabilities has become a critical challenge. Our platform simulates real-world adversarial interactions by using multiple AI personas that attempt to exploit weaknesses in AI systems. Developers can connect their AI agents through REST APIs and launch automated stress tests against predefined or custom personas. Each interaction is analyzed using an AI-powered evaluation engine that measures response quality, detects hallucinations, identifies prompt injection attempts, evaluates security risks, and generates detailed reports. Mirror AI provides an intuitive dashboard for monitoring AI health, managing personas, running stress tests, viewing analytics, and exporting comprehensive reports. The platform also supports integrations with developer workflows, making it easier to identify vulnerabilities before deploying AI systems into production. Key Features: • AI-powered adversarial personas for realistic testing • Automated stress testing of AI agents • Prompt injection and jailbreak detection • Hallucination detection and risk scoring • AI health analytics and visual dashboards • Detailed security reports and recommendations • REST API-based integration for AI applications • Scalable architecture built for modern AI development Technology Stack: Frontend: Next.js, React, TypeScript, Tailwind CSS Backend: FastAPI, Python Database: PostgreSQL State Management: Zustand Deployment: Vercel & Railway Mirror AI enables developers and organizations to evaluate, secure, and improve AI systems through automated testing and actionable insights, ultimately increasing trust and reliability in production AI applications.

VitalFlow AI is a Band-powered Multi-Agent Clinical Intelligence System designed to transform clinical reports into timely care decisions. Healthcare institutions often struggle with delayed identification of critical cases, manual report triaging, inefficient doctor assignment, missed follow-ups, and compliance tracking challenges. VitalFlow AI addresses these problems through a collaborative network of specialized AI agents that automate the entire report-to-care workflow. The platform processes diagnostic reports, extracts medical findings, evaluates patient risk, prioritizes urgent cases, routes patients to the most suitable specialists, generates explainable recommendations, schedules follow-ups, and tracks compliance activities. The system consists of 10 specialized AI agents: • Report Intake Agent • Medical Analysis Agent • Patient History Agent • Knowledge Retrieval Agent • Risk Prediction Agent • Emergency Classification Agent • Explainability Agent • Doctor Routing Agent • Notification Agent • Follow-Up Scheduler Agent Key Features: • AI Risk Assessment • Intelligent Doctor Routing • Explainable AI Decisions • Follow-Up Management • Compliance Monitoring • Escalation Management Technology Stack: Frontend: Next.js, TypeScript, Tailwind CSS Backend: FastAPI, Python Database: MongoDB Deployment: Vercel & Render AI Layer: Band Framework Multi-Agent Architecture Impact: • Faster report processing • Better prioritization of critical patients • Reduced manual workload • Improved care coordination • Enhanced compliance visibility VitalFlow AI enables hospitals, doctors, administrators, and patients to benefit from a smarter, faster, and more transparent healthcare workflow.

💻 Online Hackathon | ⏳ Build: 48 hours | 📅 September 25–27, 2026 The official IBM Bob 2.0 hackathon. Build what's next in AI-assisted development, alongside the developers and experts shaping it. ⭐ Get help from experts throughout the event 🤝 Join a team or build solo 💰 Prize pool: $12,000 🧑🏻‍💻 Register before the Kick-Off Stream to start building with Bob

🌎 Online Hackathon | 💻 Month-long challenge | Dates: Sep 1–30, 2026 | 🏆 $10,000 Prize Pool ($5k cash + $5k in AAI credits) A month-long online challenge run by lablab.ai together with AssemblyAI, the Voice AI infrastructure company for builders. Every participant builds on AssemblyAI. You can join at any point — registration stays open for the whole build window, so you can start on day one or pick the project up halfway through and still submit. 🌍 Fully online hackathon. Join and build from anywhere in the world.

🌎 Online Hackathon | 💻 Dates: 28 August–4 September 2026 | 🏆 $6,000 Prize Pool Build AI trading agents on Alpaca — autonomous agents and trading apps using Alpaca's Trading API, MCP server and CLI. 🌍 Fully online hackathon. Join and build from anywhere in the world.