
Qubic Smart Contract Studio is an AI-powered development environment that democratizes Qubic blockchain development. Our tool eliminates the $200K+ barrier of hiring specialized C++ developers by letting anyone write smart contracts in plain English. Key Features: • AI Code Generation: Natural language → production C++ contracts in seconds • FREE Security Auditing: Real-time vulnerability detection (normally $50K-150K per audit) • One-Click Deployment: Deploy to Qubic testnet/mainnet instantly • 10x Faster Development: What takes weeks now takes minutes • Monaco Editor Integration: Professional IDE experience with syntax highlighting Built specifically for Qubic's unique architecture (15.5M TPS, feeless transactions, C++ QPI contracts), our tool leverages Aigarth AI capabilities and instant finality to provide real-time feedback. ✓ Measurable Impact: $200K savings per project, 10x speed improvement ✓ Real Utility: Expands Qubic ecosystem by making development accessible to everyone ✓ Production-Ready: Full stack implementation with React frontend, FastAPI backend ✓ Post-Hackathon: Launching on Nostromo Launchpad for ecosystem funding Technical Stack: Frontend: React 18, TypeScript, Monaco Editor, Tailwind CSS, Vite Backend: FastAPI (Python), OpenAI API, Qubic SDK Infrastructure: Docker, standalone deployment with mock mode Track 1 - Nostromo Launchpad : We're building the infrastructure that helps OTHER teams move from concept → deployment → community launch. Demo: Functional IDE with AI assistant, security panel, and deployment tools.
7 Dec 2025

Core Engine: IBM watsonx Orchestrate serves as the "Brain," managing the agent's lifecycle, tool connections, and reasoning logic. We utilized the ReAct (Reason + Act) framework, allowing the agent to break down complex user queries into a chain of logical steps (e.g., Step 1: Check Budget. Step 2: Check Policy. Step 3: Formulate Answer.). Knowledge Base: A hybrid ingestion model was used. Unstructured: PDF documents for policies (Leave_Policy.pdf, Hiring_Plan.pdf) enable Retrieval-Augmented Generation (RAG) for answering qualitative questions. Structured: CSV files (employee_data.csv, recruitment_data.csv) provide the quantitative data needed for analytics. Frontend & Deployment: To demonstrate enterprise scalability, we built a custom frontend using Next.js (React). This application acts as a secure interface for the agent. Security: The app uses Next.js API Routes to securely exchange the IBM Cloud API Key for a short-lived IAM Token on the server side. This ensures that sensitive credentials are never exposed to the client browser. Hosting: The entire solution is deployed on Vercel, providing a globally accessible, responsive interface that can be used on any device. Impact & Innovation TalentPilot represents a shift from "Passive HR" to "Active Orchestration." By automating the low-level work of policy checking and data retrieval, it frees up HR professionals to focus on what really matters: people strategy and culture. It ensures 100% compliance with dynamic company rules (like hiring freezes) and provides instant, data-driven answers that would normally take a human analyst hours to compile. This project demonstrates the true potential of Agentic AI: systems that don't just talk, but help us run our businesses better.
23 Nov 2025