Vercel

Vercel is a platform designed for developers, providing speed, reliability, and scalability to create and deploy web applications. With built-in CI/CD, zero configuration, and deep integrations with popular Git providers such as GitHub, GitLab, and Bitbucket, Vercel streamlines the development process, making it easy for teams to collaborate and iterate on their projects.

General
Release date	2015
Author	Vercel
Type	Deployment and hosting platform

Tutorials

Great tutorials on how to build with Vercel

Vercel - Helpful Resources

Check it out to become a Vercel Master!

Vercel Documentation Comprehensive documentation for Vercel
Vercel Blog Stay updated with the latest news and updates from Vercel
Vercel GitHub Vercel's open-source repositories

Trifecta Checker - Blast Radius Zero

Trifecta Checker is an AI Safety Gate that prevents Lethal Trifecta attacks: when an AI agent reads private data (Gmail), fetches untrusted content (malicious URL), and tries to exfiltrate externally. How it works on Vultr: - rules/trifecta-scoring.js calculates open score 0-100: CLEAN/OK/RISKY/DANGER - rules/shield.js implements Blast Radius Zero: If agent has 3+ Lethal attempts in 1 hour, block ALL Vultr VM creation for 24h - Every block returns HTTP 403 and logs to Concordium wallet 3eLK...z44V for on-chain audit Proof on 【entity-AMD¦canonical_name=AMD】 MI300X GPU (Nov 3): Tested on notebooks.【entity-amd¦canonical_name=AMD】.com Agents 101 - Build AI Agent with MCPs using vLLM, Pydantic AI, MI300X. Safe 【entity-Airbnb¦canonical_name=Airbnb】 search = 20 CLEAN 200, Lethal read_gmail+mcp_airbnb+send_email = 100 DANGER LETHAL 403 BLOCKED. Trusted Source Scoring: .gov=100 .edu=90 concordium_verified=95 .com=40 unknown=10. Web Vault concept: Internet as persistent storage (vector DB), 【entity-AMD¦canonical_name=AMD】 ROCm model, Trifecta Safety Gate. QuantOrb-inspired open rules. Live V2: trifecta-checker-v2-eta.vercel.app GitHub: github.com/altima261/trifecta-checker (5 deploys from mobile, PC broken!) Testnet: 4BdmwCQ1yq...2QM1 (Concordium) DEV: dev.to/altima261/i-ran-trifecta-on-【entity-amd¦canonical_name=AMD】-mi300x-from-an-ipad-web-vault-proof Top 2.3% in 【entity-AMD¦canonical_name=AMD】 AI League (150/6368) - Mobile-first from Jeddah, SA.

Trifecta Checker AI Safety Gate for Lethal Agents

Trifecta Checker is an AI safety gate that blocks Lethal Trifecta attacks - the dangerous combination of Private Data + Untrusted Content + External Communication that enables data theft via prompt injection. The problem: AI agents with tools like read_gmail, browse_web, and send_email can be tricked by malicious web content to steal private emails and exfiltrate them. This is called the Lethal Trifecta. Our solution: One API call - POST /api/check-trifecta - analyzes the agent's tool manifest and returns instant verdict: - LETHAL (3/3 tools): 403 Forbidden - BLOCKED - Cannot execute - WARNING (2/3 tools): 200 OK with caution flag - SAFE (1/3 tools): 200 OK - Safe to proceed Live and tested: https://trifecta-checker.vercel.app/ - LETHAL test [read_gmail, browse_web, send_email] -> 403 - WARNING [browse_web, send_email] -> 200 warning - SAFE [read_gmail] -> 200 safe For 【entity-AMD¦canonical_name=AMD】 AI League Match 4 - Intelligent Web Information Retrieval - we extend with Trusted Source Verification: before allowing external communication, we verify web sources are trusted (.gov, .edu, Concordium ID verified). If source is untrusted, block or flag. Tech: Next.js 14 + TypeScript, Vercel Edge, Python/JS SDKs, 【entity-AMD¦canonical_name=AMD】 ROCm ready for LLM inference. GitHub: github.com/altima261/trifecta-checker. Blog: dev.to/altima261. Built by Mohammed Binashwan (altima261) from Jeddah, Saudi Arabia. Team trifecta-checker solo UTC+3. This project also registered in Concordium Trusted Agents (ZK Proofs + on-chain audit) and Vultr Agent Rush (Blast Radius Zero sandbox).

Web Retrieval Agent: Answers With Proof

Web Retrieval Agent is an AI agent that takes a plain-English question, searches the live web, reads the actual pages and returns only the specific information the user asked for, together with the exact quote that proves it. Most AI search tools write a fluent answer and ask you to trust it. This agent treats the language model as untrusted. It plans targeted search queries, uses Tavily to search and extract full page text, and asks the LLM (gpt-oss-120b on Groq) for a structured answer with verbatim evidence quotes. The server then checks every quote against the real page text and drops any that do not appear. If the answer contains a figure that the quotes do not support, confidence is lowered and the user is warned. If the sources do not contain the answer, the agent says so instead of guessing, and it can retry once with refined queries focused on a likely site. The interface streams the agent's activity live (planning, searching, reading, verifying), then shows the answer, a confidence meter, the proof quotes with source links and every source checked. It is built with Next.js and TypeScript and deployed on Vercel. The LLM client works with any OpenAI-compatible endpoint, so the model can be swapped for an open model served on AMD GPUs.

DocuPilot AI: Smart Docs & AI Asst.

DocuPilot AI by Tech_Innovators streamlines document processing and knowledge management for businesses. It tackles manual data extraction, inefficient searching, and verification challenges in documents like invoices, contracts, and reports. The platform integrates document extraction, intelligent search, invoice analysis, automatic classification, and human review. Users can upload documents, extract text, query content, and inspect original evidence securely. Key Features: 1. **Intelligent Document Extraction:** Extracts text from PDFs, images, and TXT. 2. **Evidence-Grounded Q&A:** Provides answers with source references and evidence. 3. **Invoice Intelligence:** Extracts invoice data, performs checks, and generates financial reports. 4. **Explainable Document Classification:** Auto-categorizes documents with traceable evidence. 5. **Human-in-the-Loop Verification:** Allows users to correct and approve extracted data. 6. **Private Document Management:** Ensures security with authentication and authorization. 7. **Optional Asynchronous Processing:** Supports background extraction with job tracking. Built with modern web technologies, DocuPilot AI emphasizes trustworthy workflows by linking information to original evidence and enabling human verification. It's ready for hackathon submission and demonstrations; public deployment requires further security validation.

Keepmine-AI

KeepMine AI is an AI-powered conversation memory and information retrieval platform designed to help users turn overwhelming chat histories into searchable, useful knowledge. Important information is often buried in long conversations, making it difficult to remember payment details, find customer requests, track orders, retrieve delivery information, or recall previous agreements. KeepMine AI addresses this problem by helping users access relevant information from their conversations quickly and efficiently. The platform aims to transform everyday messaging into a practical knowledge base, reducing the time spent scrolling through old messages and minimizing the risk of missing important details. By combining artificial intelligence with conversational search, KeepMine AI makes it easier to find what matters when it matters. Our vision is to make digital conversations more organized, searchable, and valuable for individuals, entrepreneurs, and businesses that rely on messaging for communication and daily operations.

ShipRAG

ShipRAG (Freight Command) is an enterprise-grade autonomous logistics intelligence platform engineered to streamline global supply chain visibility, paperwork verification, and exception management across ocean, air, and road freight operations. Built on a robust FastAPI and React architecture, ShipRAG continuously monitors end-to-end shipment milestones and calculates dynamic risk scores based on operational delays, carrier performance, and critical customs deadlines. The platform integrates a deterministic document processing engine that extracts structured data from commercial invoices, packing lists, and bills of lading, performing cross-document weight reconciliation to catch legal discrepancy holds before cargo arrives at customs inspection points. When operational bottlenecks or customs discrepancies occur, ShipRAG deploys an autonomous AI reasoning agent. Using strict safety fences and domain-specific tool-calling mechanisms, the agent diagnoses root causes, generates mitigation strategies, and dispatches proactive stakeholder advisories. High-consequence interventions—such as freight re-routing, delivery milestone adjustments, or workflow escalations—are routed directly through a dedicated Human Approval Gateway (RULE-E06 Governance Gate). This guarantees that human operators maintain oversight and sign-off authority while preserving an immutable, compliance-grade audit trail across all automated decisions.