Top Builders

Explore the top contributors showcasing the highest number of app submissions within our community.

xAI

xAI is an innovative AI technology company founded by Elon Musk in July 2023. The company is dedicated to pushing the boundaries of artificial intelligence by creating tools and platforms to advance scientific discovery, foster understanding, and simplify complex problem-solving. With cutting-edge technology and a user-focused approach, xAI provides developers and organizations with the tools they need to unlock the potential of AI in everyday applications.

General Information

AttributeDetails
CompanyxAI
Founded2023
Documentationhttps://docs.x.ai/docs
API Referencehttps://docs.x.ai/api#introduction

Products

Grok AI Models

xAI's flagship product line consists of the Grok series of conversational AI and vision-enhanced models:

  • Grok-1: xAI's foundational model offering robust reasoning and conversational capabilities.

  • Grok-1.5: Improved reasoning and extended context for handling large datasets.

  • Grok-1.5V: Introduced vision capabilities for analyzing images and diagrams.

  • Grok-2: Enhanced performance with advanced image generation and multimodal abilities.

xAI API

An accessible platform for developers to integrate Grok models into their applications. Fully compatible with existing OpenAI and Anthropic SDKs.

PromptIDE

A powerful integrated development environment for crafting, testing, and refining AI prompts. Designed to optimize prompt engineering workflows for large language models.

Start Building with xAI

👉 Visit x.ai to create a developer account and get started.

👉 Sign in to the xAI Developer Portal to obtain API keys, access Grok models, and explore documentation.

Edit on GitHub

xAI AI Technologies Hackathon projects

Discover innovative solutions crafted with xAI AI Technologies, developed by our community members during our engaging hackathons.

Resume Compact

Resume Compact

Resume Compact, the HR Resume Analyzer, is an intelligent, end-to-end recruitment automation platform designed to streamline candidate screening and evaluation by combining modern document processing, artificial intelligence, and web technologies to eliminate manual resume review bottlenecks and provide data-driven hiring insights to recruitment teams. Key technical features include seamless fallback PDF processing with transition from native text extraction to OCR when needed, LangChain structured output using StructuredPrompt and Pydantic to ensure JSON-compliant responses, strict schema enforcement that validates all outputs against Pydantic models and rejects malformed responses, detailed and context-rich prompt engineering to guide the LLM toward accurate structured analysis, async HTTP using httpx for efficient non-blocking calls to the LLM API, robust exception handling with informative HTTP status codes and error messages, and comprehensive audit logging with timestamps, file IDs, and LLM raw responses stored for compliance and debugging. The system reduces recruitment cycle time by 60-80%, eliminates subjective bias in initial screening, allows HR teams to focus on relationship-building rather than document review, and, by standardizing candidate data into structured JSON, enables downstream analytics, reporting, and integration with ATS (Applicant Tracking Systems).

Proof Of Thought

Proof Of Thought

make description of that 100 words The Nano Payment Project is a production-ready fintech solution designed with a hyper-minimalist aesthetic and high-performance architecture. Built using Next.js, FastAPI, and Tailwind CSS, it streamlines digital transactions through a clean, distraction-free interface. The project integrates an Agentic AI layer to provide users with real-time transaction insights and automated support. Optimized for WSL2 environments, it features robust security via JWT, seamless dark mode, and a responsive mobile-first design. This system bridges the gap between complex financial workflows and end-user simplicity, offering a scalable blueprint for modern SaaS applications and efficient, "one-tap" payment processing. 🚀💸

Soliris Arc

Soliris Arc

Soliris Arc is the reference agentic-economy stack on Arc L1 (chain 1516, Circle's USDC-native EVM chain). Trading agents purchase real-time signals from a Signal Server for $0.001 USDC per request, paid via Circle Nanopayments and verified on-chain through the Circle Wallets API. Each signal purchase autonomously triggers a sub-payment from the Signal Server to an upstream data-feed agent — a 3-layer machine-to-machine payment chain that runs every 60 seconds with zero human intervention. Live state (Arc testnet): - 500+ Arc transactions settled - 250 signal purchases + 250 data-feed sub-payments - Real Circle Nanopayments

AgentInvoice

AgentInvoice

The agentic economy is here. AI agents are making decisions, calling APIs, and completing tasks autonomously. But there's a missing layer: how do agents pay for the data they consume? AgentInvoice is that layer. We built payment middleware that wraps any API and adds per-call micropayments via Circle Nanopayments on Arc. When an AI agent calls a paid endpoint, the middleware intercepts the request, processes a USDC nanopayment on Arc, confirms the transaction on-chain, and returns the response - all in under 5 seconds. The problem: Traditional billing (Stripe, subscriptions) is designed for humans. It requires accounts, credit cards, monthly cycles, and $0.30 minimum fees. None of this works for AI agents making 1,000 API calls per hour at $0.001 per call. What we built: - Payment middleware that intercepts API calls and processes Circle Nanopayments - Three demo paid APIs: weather ($0.001), summarize ($0.005), sentiment ($0.002) - Budget enforcement: middleware blocks payments when agent exceeds spending limit - AI agent demo: Grok autonomously decides what data it needs, pays for it, and completes tasks end-to-end The demo shows Grok receiving a task, calling three paid APIs, paying for each autonomously, hitting a budget wall on a complex task, getting blocked by the middleware, and adapting - all without human involvement. Every payment is verified on Arc Block Explorer. Why this matters for Arc: every API call equals one Arc transaction. 1,000 developers × 10,000 calls/day = 10 million transactions/day on Arc. AgentInvoice is the developer onboarding ramp and transaction volume engine for the agentic economy. Tech stack: Node.js, Express, Circle App Kit, @circle-fin/adapter-viem-v2, Viem, Grok API (xAI), Arc Testnet.

Arc Climate Pay

Arc Climate Pay

Arc Climate Pay is a fully on-chain parametric weather insurance protocol built on Arc Network Testnet. Users purchase USDC-denominated policies against real climate conditions — frost, heat, heavy rain, drought, and high wind. When the on-chain oracle confirms a trigger, the smart contract executes the payout automatically. No claims process. No adjusters. No waiting. Just code. HOW IT WORKS Users connect their wallet and select a city (11 global cities supported), risk type, threshold, premium (5–20 USDC) and duration (7, 10 or 30 days). A weather oracle running 24/7 fetches real data from Open-Meteo API and writes it to the WeatherOracle contract every 10 minutes. When the condition is met, the payout executes instantly in USDC — no manual action required. AI AGENT & NANO-PAYMENTS The core innovation is the built-in AI agent powered by Groq (llama-3.3-70b-versatile). For just 0.01 USDC paid on-chain, the agent analyzes live oracle weather data and recommends optimal policy parameters. User pays → AI analyzes → policy deploys in two clicks. Arc's predictable USDC fees and sub-second finality make this micro-payment model economically viable at scale — exactly what the agentic economy requires. WHAT THIS UNLOCKS Climate risk is underfunded in DeFi. Farmers, businesses and individuals face real weather exposure — but traditional insurance is inaccessible, expensive and slow. Arc Climate Pay makes parametric weather protection available to anyone with a wallet. Combined with AI-powered policy generation at 0.01 USDC per query, it demonstrates that the agentic economy is already working on Arc Network today. COVERAGE 11 cities: Istanbul, New York, London, Tokyo, São Paulo, Seoul, Paris, Berlin, Dubai, Sydney, Mumbai. 5 risk types: Frost, Heat, Heavy Rain, Drought, High Wind. Premium: 5–20 USDC · Payout: up to 1.9× net premium · Duration: 7, 10 or 30 days.

Barzakh AI

Barzakh AI

Barzakh AI it's a fully operational Machine-to-Machine (M2M) micro-economy. We've engineered a decentralized swarm of AI agents that autonomously buy and sell financial intelligence via high-frequency, sub-cent nanopayments on the Arc Testnet. Here's how the autonomous intelligence pipeline works in real-time: Step 1 — The Request A user submits a prompt: "I'm seeing conflicting signals on $WIF. Query the Signal Agent, check multi-timeframe data. If it's dumping on the 1H but profitable on the 30D and 1Y, I want to catch the knife — give me a risk-adjusted entry, stop loss, take profit, and a definitive LONG or SHORT signal." Step 2 — Autonomous Data Aggregation The Orchestrator Agent intercepts the intent and, lacking quantitative context, autonomously queries external APIs to gather multi-timeframe price data (1H, 24H, 30D, 1Y, ATH, ATL) alongside the asset's visual chart feed. Step 3 — On-Chain Nanopayment To access the proprietary Signal Agent microservice, the Orchestrator must pay a strict inference fee of 0.002 USDC. Using Smart Wallets and Viem, it autonomously signs and broadcasts the transaction on Arc Testnet — seamlessly, in the background. Step 4 — Verification & Inference The Signal Agent verifies the on-chain transaction hash, then executes a multimodal prompt via Gemini 3.1 Pro — synthesizing visual chart data with quantitative inputs to output a precise JSON trade setup. Step 5 — Execution The Orchestrator delivers a definitive LONG/SHORT signal with a risk-adjusted entry price, take profit, and stop loss — plus a clickable Arcscan receipt proving the background payment occurred. Economic Reality The inference fee is 0.002 USDC. On Ethereum mainnet or standard L2s, gas alone ($0.10–$2.00+) would cost 50×–1000× more than the product itself. Arc reduces overhead to near-zero, enabling agents to trade data profitably at high frequency — proven by our load-test executing 50+ consecutive intelligence payments without friction.