Top Builders

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

GitHub

GitHub is a cloud-based developer platform built on Git, launched publicly in April 2008 by Tom Preston-Werner, Chris Wanstrath, P.J. Hyett, and Scott Chacon. Acquired by Microsoft in 2018 for $7.5 billion, it has grown into the central hub of open-source software and professional software development, hosting over 100 million developers worldwide. Beyond code hosting, GitHub now offers a full suite of tools spanning CI/CD automation, security analysis, cloud development environments, and AI-powered coding assistance through GitHub Copilot.

General
CompanyGitHub, Inc.
FoundedApril 2008 by Tom Preston-Werner, Chris Wanstrath, P.J. Hyett, Scott Chacon
Acquired byMicrosoft (October 2018, $7.5B)
HeadquartersSan Francisco, California, USA
Websitegithub.com
Documentationdocs.github.com
GitHubgithub.com/github
TypeDeveloper Platform

Core Products

GitHub Repositories and Code Hosting

The foundation of GitHub: Git-based version control with pull requests, code review workflows, branch protections, and merge strategies. Supports public, private, and internal repositories at any scale.

GitHub Copilot

An AI-powered coding assistant providing inline completions, chat, autonomous agent mode, and cloud-based coding agents. Available across VS Code, JetBrains, Xcode, Eclipse, Neovim, and GitHub.com itself.

GitHub Actions

A CI/CD and workflow automation platform built into every repository. Write YAML-defined workflows triggered by events (push, PR, schedule) and run them on GitHub-hosted or self-hosted runners.

GitHub Advanced Security

Security tools including secret scanning, code scanning (CodeQL static analysis), and Dependabot for dependency vulnerability management. Available on GitHub Enterprise Cloud and as add-ons for Teams.

GitHub Codespaces

Cloud-hosted development environments that spin up a full VS Code workspace in seconds, pre-configured from a devcontainer.json in the repository.

GitHub Spark

A natural-language app builder (public preview) that generates and deploys full-stack web applications from a prompt, integrated with Copilot.

Developer Resources

GitHub's developer ecosystem spans official SDKs, REST and GraphQL APIs, GitHub Apps, OAuth Apps, and Actions marketplace extensions.

Key Features

Integrated AI with Copilot GitHub Copilot is embedded natively across GitHub.com, the CLI, and major IDEs. It supports multi-model selection (OpenAI, Anthropic Claude, Google Gemini), autonomous agent mode, and MCP server integrations.

Actions-native CI/CD GitHub Actions offers thousands of pre-built actions in the Marketplace, matrix builds, reusable workflows, and first-class integration with every GitHub event.

Security-first by default Dependabot monitors dependencies for CVEs and auto-opens fix PRs. Secret scanning alerts on accidentally committed credentials. CodeQL catches security vulnerabilities before they ship.

Use Cases

Open-Source Collaboration GitHub hosts the majority of the world's public open-source projects, providing issue tracking, discussions, wikis, GitHub Pages, and Sponsors for maintainer funding.

Enterprise Software Delivery GitHub Enterprise Cloud adds SSO, audit logs, compliance controls, IP allowlists, and dedicated support, making it the platform of choice for regulated industries and large engineering organizations.

Edit on GitHub

Github AI Technologies Hackathon projects

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

AI Classroom Edge Intelligence

AI Classroom Edge Intelligence

AI Classroom Edge Intelligence is a privacy-first classroom AI platform built for schools that need useful AI without sending every piece of student information to the cloud. The platform evaluates each task by privacy level, connectivity, and complexity, then routes it to Offline Edge Mode, a Local Classroom Server, or Fireworks AI Cloud Assist. Sensitive or restricted information stays local. Eligible anonymized, high-complexity tasks are sent through a secure Express backend to Fireworks Serverless using Qwen3.7 Plus. The project includes an AMD Model Router, Edge Runtime Monitor, Rural Connectivity Simulator, Privacy and Local Data Ownership Console, Classroom Digital Twin, and teacher approval workflow. Live results display the provider, model, route, privacy classification, latency, safety note, and AI response. API keys remain server-side, and the privacy guard blocks sensitive requests from cloud inference. The project was inspired by rural schools where connectivity can be unreliable and student privacy is critical. Instead of acting as a simple chatbot, it serves as an intelligent routing and decision-support system. Teachers review, edit, approve, or reject recommendations before instructional actions are recorded. The current implementation includes a working browser interface, real backend routing, live Fireworks Serverless integration, server-side key protection, and Docker containerization. Local AMD AI PC inference, GPU/NPU acceleration, device telemetry, and production synchronization are clearly identified as future work. The long-term vision is a school-owned AI platform combining local intelligence, optional cloud reasoning, persistent classroom evidence, and teacher oversight for rural and underserved communities.

Verity — Fact-Checking for the Rest of Us

Verity — Fact-Checking for the Rest of Us

Most people believe first and verify never , there simply isn't time to check every headline, post, or forwarded message before deciding whether to trust it. That gap is where misinformation lives and spreads. Verity closes it. You give Verity a claim — a headline, a statistic, a line from an article — and it separates what's actually checkable from what's just opinion, then searches for independent evidence across 40+ public authoritative sources. Instead of trusting a single model's best guess, Verity requires independent checks to agree before returning a verdict: true, false, or somewhere in between, with a source trail you can click through and verify yourself. Every verification runs live on AMD Instinct hardware via the Fireworks AI API, using Gemma and other open-source models routed through a 5-pass consensus architecture — nothing pre-computed, nothing faked. The models are swappable and inspectable by design, because a trust tool that asks you to trust it blindly defeats its own purpose. Verity is built for the moment right before someone shares something they haven't checked , turning fact-checking from a newsroom luxury into something anyone can do in seconds.

Contxt

Contxt

Every AI grew a memory in 2026 — ChatGPT, Claude, Gemini, Copilot, Grok — but they're five walled gardens that never talk to each other, so you re-introduce yourself every time you switch. And every memory product (Mem0, Supermemory, Letta) is cloud-first and built for developers, not for you. Contxt is the consumer piece nobody built: one portable, privacy-first context layer that works across every AI, where your most sensitive data never leaves your device. A browser extension connects your Gmail, Calendar and Notion, then classifies every item on-device through a Crown-Jewels Gateway — Gemma 3 270M running in WebGPU plus a deterministic-rules safety floor. PRIVATE "crown jewels" stay local and end-to-end encrypted (the cloud is a blind relay of ciphertext, with keys transferred device-to-device by QR). SHARED context is distilled into reusable cards that any AI can read over MCP, and injected live into the composer on Claude, ChatGPT and Gemini. A companion web dashboard mirrors the extension in real time. One context layer. Every AI. Your data stays yours.

SecondChance AI

SecondChance AI

SecondChance AI is an AI-powered relationship recovery and meaningful connection platform designed for people rebuilding their lives after difficult relationships, heartbreak, divorce, or emotional setbacks. Instead of focusing only on dating, our platform prioritizes emotional healing, confidence building, safety, and meaningful human connections through artificial intelligence. The platform combines intelligent profile analysis, AI-assisted compatibility insights, personalized relationship coaching, guided onboarding, secure matching, and a clean user experience to help users confidently begin a new chapter in life. Every recommendation is designed to encourage healthy communication, emotional well-being, and long-term compatibility rather than superficial interactions. Our AI Coach acts as a supportive companion that provides personalized guidance, emotional encouragement, reflective conversations, and practical relationship advice. The matching system analyzes interests, goals, personality traits, and compatibility signals to recommend meaningful connections. Additional features such as profile management, secure messaging, privacy-focused settings, and guided onboarding create a complete recovery-to-relationship journey. SecondChance AI is built with scalability and privacy in mind using modern technologies including React Native, Expo, Firebase, TypeScript, and AI-driven recommendation logic. Alongside the mobile application, we developed a premium landing website showcasing the vision, product experience, roadmap, and future plans for the platform. Our long-term vision is to evolve SecondChance AI into a trusted global relationship wellness ecosystem where artificial intelligence not only helps people discover compatible partners but also supports emotional healing, relationship education, communication improvement, and healthier human connections. We believe everyone deserves a second chance to heal, grow, and build meaningful relationships with confidence.

ReCodeX

ReCodeX

ReCodeX is an AI-powered enterprise platform developed for the AMD Developer Hackathon: ACT II (Track 3 - Unicorn Track) designed to tackle the multi-billion dollar challenge of technical debt and legacy migration. Instead of a basic chatbot conversational layout, ReCodeX provides a complete engineering dashboard that automates the analysis, documentation, translation, and verification of aging infrastructure like legacy Java, COBOL, or unoptimized C++. The platform delivers comprehensive developer features, including: - Side-by-Side Modernization: Allows users to upload a legacy source file and view the original code side-by-side with refactored, modern, and fully test-covered code. - Automated Documentation: Provides deep semantic understanding of complex code logic to break down precisely what legacy components do. - Risk & Security Audits: Automatically generates a comprehensive Risk Report highlighting structural changes, security optimizations, and cloud-readiness metrics. The AMD Advantage & Tech Architecture: - To process heavy enterprise code demands reliably, ReCodeX relies entirely on high-performance cloud infrastructure backed by AMD hardware. - Core LLM orchestration is routed via the Fireworks AI API, utilizing high-performance AMD hardware endpoints running Google DeepMind's open-source Gemma models. - The compute layer is hosted on the AMD Developer Cloud, leveraging powerful cloud-based AMD GPUs to manage parallelized analytics, code scanning, and workflow pipeline tasks at sub-second latencies. - The entire system is packaged inside a Docker container for standardized deployment, with the frontend application built using Streamlit and React. Ultimately, ReCodeX targets tangible enterprise metrics for the Unicorn Track by reducing ongoing maintenance overhead, ensuring regulatory auditability through precise change logging, and accelerating cloud migration frictionlessly.

Curio

Curio

Paste this at the end of the text you already have: Development Philosophy During the development of Curio, our primary focus was on "Time-to-Value." We understood that in a fast-paced hackathon environment, the ability to iterate quickly and show tangible results is paramount. By leveraging the latest Google GenAI SDK, we were able to abstract away complex model interactions and focus on creating a user experience that feels premium and responsive. The decision to integrate marked.js was born out of a necessity to present AI-generated content in a human-readable format, bridging the gap between raw data and actionable information. Our development process involved rigorous testing of the frontend-backend communication, ensuring that even under high load or potential API timeout scenarios, the application remains stable and visually consistent. Future Roadmap While Curio is already a functional intelligence platform, we envision several paths for future development to enhance its impact: Multi-Modal Integration: Expanding beyond text to provide video summaries and audio-briefing capabilities for users on the go. Granular Preference Learning: Implementing an automated feedback loop where the AI learns from the articles a user clicks on, refining its filtering logic over time to become increasingly accurate. Enterprise Customization: Creating a B2B version of Curio that allows companies to ingest internal company news and market reports, providing employees with a personalized feed of internal announcements alongside industry trends. Global Language Support: Expanding the linguistic capabilities of the Gemini model integration to serve non-English speaking markets, ensuring that personalized news is accessible regardless of the user's primary language.

GitHub