🤝 Top Collaborators
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🤓 Latest Submissions
VoxArchitect — Voice-Native Intelligence
# VoxArchitect Voice-native enterprise architecture and change intelligence built for the AssemblyAI Voice Agent Hackathon. VoxArchitect lets an architect speak a change request, inspects repository/system evidence, maps dependencies, reasons about architecture and security impact, drafts ADRs, and stages GitHub actions behind an explicit human approval gate. ## Architecture - **Frontend:** React + Vite, browser microphone capture, 24 kHz PCM AudioWorklet, AssemblyAI Voice Agent WebSocket, live transcript, evidence/graph view. - **Backend:** FastAPI REST API for temporary AssemblyAI tokens, tool dispatch, orchestration, GitHub integration, approval-gated actions and knowledge/evidence storage. - **Agents:** Intent Router, Repo Scout, Dependency Mapper, Architecture Analyst, Trust Reviewer and Delivery Agent coordinated by a deterministic orchestrator. - **LLM:** Optional AssemblyAI LLM Gateway (OpenAI-compatible). The app still runs in demo/fallback mode without credentials. - **Hosting:** Docker Compose. Nginx serves the built frontend and reverse-proxies `/api` to FastAPI.
30 Sep 2026
Autonomous Unified Risk & Alpha Agent
**AURA (Autonomous Unified Risk & Alpha Agent)** is an autonomous AI trading agent designed to make trading decisions that are explainable, bounded, and fully auditable. It combines probabilistic LLM-powered reasoning with a deterministic risk engine that the AI cannot override. For every trading opportunity, AURA uses a four-stage pipeline: the **Market Agent** analyzes technical indicators such as SMA, RSI, MACD, and ATR; the **Strategy Agent** develops a BUY, SELL, or HOLD trade thesis; the **Critic Agent** performs adversarial self-critique by actively attempting to identify weaknesses in the proposed trade; and finally, the **Deterministic Risk Engine** independently validates confidence, risk/reward, position size, and portfolio exposure before approving or rejecting the trade. Approved decisions can be executed through the **Alpaca paper-trading API**, while every decision—including rejected trades—is stored in SQLite as a replayable audit trail. Built with **Python, Groq LLMs, Alpaca, Pandas, SQLite, and Streamlit**, AURA also includes a dashboard for monitoring autonomous trading activity. The project is designed as a research prototype demonstrating how AI agents can operate safely in high-stakes environments by separating AI reasoning from deterministic governance.
4 Sep 2026
NexGen AOS
NexGen AOS Autonomous Supply Operating System NexGen AOS is an AI-native, multi-agent operating system for autonomous supply-chain and enterprise operations. It connects procurement, demand, inventory, suppliers, logistics, warehouses, finance, risk, and executive decision-making into one continuously operating agentic platform. Its core distinction is that it moves beyond BI → recommendations → autonomous action: Observe → Understand → Predict → Plan → Decide → Approve → Execute → Verify → Learn The full version should expand to roughly 25–30 agents across five layers: Command: Executive, Supervisor, Planner, Policy/Governance and Human-Approval agents. Supply Intelligence: Demand Forecasting, Inventory Optimization, Supply Planning, Scenario Simulation and Disruption Prediction agents. Procurement: Sourcing, Supplier Intelligence, RFQ, Negotiation, Contract Intelligence, Purchase Order and Procurement Compliance agents. Fulfilment: Logistics, Shipment Tracking, Warehouse, Route Optimization, Exception Management and Returns agents. Enterprise Control: Finance, Cost Optimization, Risk, Fraud/Anomaly, ESG, Analytics, Reporting, Audit and Learning agents.
10 Aug 2026
AI Real Estate Marketplace with Smart Agent
This project is an AI-powered real estate marketplace designed to simplify how people buy and sell property. The platform acts as a centralized digital hub where multiple sellers list properties and customers search, compare, and transact—all in one place. The core innovation is an intelligent AI real estate agent embedded into the website. This agent interacts with users, understands their specific requirements such as budget, location, property type, and preferences, and then intelligently recommends the most relevant properties. Instead of manually browsing hundreds of listings, users receive personalized, data-driven suggestions in real time. The platform works as a neutral intermediary rather than a traditional broker. It increases transparency, reduces misinformation, and helps users avoid scams by providing verified listings and guided decision-making. Sellers benefit from better visibility and targeted buyers, while customers gain a faster, smarter, and more secure property discovery experience. Overall, this solution modernizes the property market by combining AI, automation, and a marketplace model to create a more efficient, user-friendly, and trustworthy real estate ecosystem.
7 Feb 2026
