
Reef is a comprehensive AI agent workflow platform that democratizes the creation and deployment of multi-agent systems. Built on Coral Protocol, Reef enables developers to visually design, test, and deploy intelligent agent workflows without complex coding. Key Features: - Visual Workflow Canvas: Drag-and-drop interface for designing agent interactions with real-time preview - Agent Orchestration: Seamlessly coordinate multiple AI agents using Coral Protocol's zero-trust API - Service Integration: Native support for popular tools (Slack, GitHub, LinkedIn, Notion, Jira) - Real-time Collaboration: Live chat interface for iterating on workflows with AI assistance - One-Click Deployment: Export and run workflows instantly on the Coral ecosystem The platform features an elegant, responsive design with: - Clean agent node visualization showing tools, connections, and data flow - Independent scrolling areas for optimal UX - Smart tool icon detection for 9+ popular services - Professional workflow canvas with ReactFlow integration Reef addresses the complexity barrier in multi-agent development by providing an intuitive visual interface while maintaining the power and flexibility of Coral Protocol's agent orchestration capabilities. Developers can focus on business logic rather than infrastructure, accelerating the development of intelligent applications. Built with Next.js, TypeScript, Tailwind CSS, and integrated with Coral Protocol for seamless agent management and deployment.
21 Sep 2025

Have you heard of Soham? In a world where hiring fraud is harder to detect, how can you identify bad actors quickly and affordably? We’re team Le Commit, and we built Unmask for the Vultr track after seeing how easy it’s become to fake resumes, reuse identities, and vibecode technical interviews. Fast-moving teams don’t have time for slow, outdated background checks, and the cost of a bad hire is too high. Unmask is an AI-powered credibility checker that helps hiring managers verify candidate authenticity by detecting inconsistencies across CVs, LinkedIn, GitHub, reference calls, and live interviews. It flags timeline mismatches, missing signals, and potential identity fraud. Reference calls are automated using voice APIs, with transcripts scored and cross-checked against prior claims. During interviews, Unmask provides real-time prompts to validate risky areas. The dashboard surfaces credibility scores, red/yellow flags, and suggested follow-ups, giving teams signal before they waste time. Built with LLaMA models, Groq API, React, Tailwind, and deployed on Vultr using a modular agent pipeline. Like at http://unmask.click/ Repo https://github.com/mousberg/le-commit
8 Jul 2025