Top Builders

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

Gemma 2

Gemma 2 is the second-generation open large language model (LLM) from Google, built to advance performance, scalability, and responsible AI development. This model family supports diverse applications, from complex conversational AI to advanced content moderation systems. Based on Google’s leading transformer architecture, Gemma 2 builds on the Gemma foundation, incorporating enhanced safety, accessibility, and multi-platform deployment capabilities.

General
Relese dateFebruary 2024​
AuthorGoogle DeepMind in collaboration with Google AI teams
WebsiteGoogle AI Gemma
RepositoryGoogle AI Developer Resources​
TypeAdvanced open-source AI, large language model

Key Features:

  • Enhanced Parameter Options: Gemma 2 is available in configurations up to 27 billion parameters (2B, 9B, and 27B) for handling large-scale, complex language tasks​.

  • ShieldGemma Safety Classifiers: ShieldGemma, a suite of safety-focused classifiers, helps detect and mitigate harmful content, addressing issues like hate speech, harassment, and explicit material.​

  • Efficient Transformer Architecture: Supports processing up to 8192 tokens in a single pass, enhancing performance in long-form text processing and providing nuanced output across complex language tasks​.

  • Flexible, Scalable Deployment: Optimized for both edge devices and cloud infrastructure, making it suitable for local, distributed, and high-demand deployment environments​.

  • Integration with Leading AI Platforms: Works seamlessly with Google Cloud’s Vertex AI, Keras, JAX, and PyTorch, providing adaptable and efficient customization options for developers​.

Applications:

  • Enterprise AI: Suitable for high-scale, complex applications such as automated data analysis, market predictions, and large-scale content creation.

  • Content Moderation Systems: The ShieldGemma classifiers filter harmful content, making it a good choice for moderation in social media, online communities, and customer service settings​.

  • Multilingual Applications: With enhanced token processing, Gemma 2 is optimal for tasks requiring intricate language understanding and cross-language generation, ideal for global customer support and translation tools.

  • Conversational AI and Chatbots: Instruction-tuned models within Gemma 2 make it highly effective for advanced conversational systems, chatbots, and interactive voice assistants​.

Get started building with Gemma 2:

You can start developing with Gemma 2 by accessing model weights from Google AI Studio and Kaggle. With integrated ShieldGemma safety tools, the model is prepped for responsible and large-scale deployments. The model’s compatibility with Google Cloud, Vertex AI, and popular AI frameworks makes it easy to customize for both edge and cloud solutions. Explore the full suite of resources on Google AI Gemma to unlock the potential of Gemma 2 and build robust, responsible AI applications​.

Google Gemma 2 AI technology Hackathon projects

Discover innovative solutions crafted with Google Gemma 2 AI technology, developed by our community members during our engaging hackathons.

OpenMind Nexus: Cognitive Risk Intelligence

OpenMind Nexus: Cognitive Risk Intelligence

OpenMind Nexus is a multi-agent cognitive risk investigation platform that helps organizations identify, analyze, and respond to information integrity incidents. Modern organizations face increasing risks from disinformation, manipulated narratives, synthetic media, and persuasive content designed to influence decision-making. Investigating these threats is often manual, fragmented, and difficult to scale. OpenMind Nexus transforms this process into a collaborative workflow powered by Band. When suspicious content is submitted, specialized AI agents collaborate through a shared investigation room: • Content Intake Agent – Structures content and creates investigation artifacts. • Cognitive Bias Agent – Detects manipulation patterns, cognitive biases, and persuasion techniques. • Verification Agent – Evaluates credibility, unsupported claims, and evidence quality. • Echo Chamber Agent – Measures amplification and polarization risks. • Explainability Agent – Combines findings into a transparent reasoning trace and recommendation. Instead of relying on a single AI response, agents contribute independent evidence into a shared context. Recommendations emerge from multiple evidence streams. The platform supports three outcomes: • ARCHIVE – Low-risk content. • MONITOR – Ambiguous content requiring observation. • ESCALATE – High-risk incidents requiring Trust & Safety, Compliance, or Security review. Band serves as the collaboration layer, enabling agents to exchange structured context, maintain investigation state, and participate in auditable workflows. By separating reasoning from transport, OpenMind Nexus creates a scalable architecture for enterprise investigations. By combining bias detection, credibility analysis, polarization assessment, explainability, and human oversight, OpenMind Nexus demonstrates how organizations can move beyond single-agent AI systems and adopt transparent, collaborative AI investigations.

AluminatiEye

AluminatiEye

AluminatiEye is a GPU Cloud Intelligence Oracle built to help AI teams make smarter infrastructure decisions in an increasingly complex GPU market. Today, AI builders face fragmented cloud providers, constantly changing GPU pricing, infrastructure shortages, and limited visibility into which provider is the best fit for a workload. Teams often spend hours comparing vendors, researching companies, monitoring pricing, and evaluating risk before deploying models. AluminatiEye creates a unified intelligence layer across the GPU ecosystem. The platform collects and analyzes data from multiple GPU cloud providers and public sources to generate actionable infrastructure insights. Key capabilities include: • Live Pricing – Tracks GPU pricing across multiple cloud vendors in real time. • Arbitrage Detection – Finds cost-saving opportunities between providers. • Market Intelligence – Aggregates news, sentiment, regulations, and competitive signals. • Risk Scores – Evaluates providers based on reliability, growth, uptime, and market health. • Cost Calculator – Estimates infrastructure spending. • Recommender – Suggests optimal GPUs and providers for training, fine-tuning, inference, and image generation workloads. • Oracle Engine – Combines all signals into a single recommendation. Built using Bright Data's web intelligence infrastructure, AluminatiEye transforms raw infrastructure data into strategic recommendations that help organizations reduce costs, mitigate risk, and make faster infrastructure decisions. Our vision is to become the intelligence layer for the GPU economy, giving founders, engineers, researchers, and AI teams a single source of truth for cloud infrastructure decisions.

CodeSage — AI DevSecOps Intelligence

CodeSage — AI DevSecOps Intelligence

CodeSage is an enterprise-grade AI-powered DevSecOps and deployment intelligence platform built for the Web Data UNLOCKED hackathon. Traditional static analyzers detect vulnerabilities in isolation using stale databases and limited contextual awareness. CodeSage goes significantly further by combining AI-powered code reasoning with realtime web threat intelligence to determine whether software is truly safe for production deployment. The platform acts as an autonomous CI/CD security gatekeeper. Users can upload ZIP repositories or connect GitHub projects directly. CodeSage recursively analyzes multi-file, multi-language codebases using a specialized multi-agent architecture powered by OpenRouter models including Llama 3.1, Mistral, and DeepSeek. The platform detects: * OWASP vulnerabilities * runtime risks * insecure dependencies * hardcoded secrets * SQL injection vulnerabilities * weak cryptography * insecure upload flows * architectural security risks * deployment blockers What makes CodeSage unique is its integration with Bright Data’s realtime web intelligence infrastructure. When vulnerabilities are detected, CodeSage uses: * Bright Data SERP API * Web Unlocker * Scraping Browser to investigate live exploit activity across CVE databases, GitHub advisories, security discussions, and protected vulnerability sources across the public web. This enables the system to determine: * whether a vulnerability is actively exploited, * whether dependencies are associated with live CVEs, * and whether production deployment should be blocked immediately. CodeSage then: * generates AI-powered remediation patches, * updates realtime security scores, * streams live scan progress using Supabase Realtime, * and delivers a final deployment verdict: * PASS * WARN * BLOCK By combining autonomous AI reasoning with realtime web intelligence, CodeSage transforms security from a reactive bottleneck into a live deployment intelligence system for modern software teams.

Rex Intel Services

Rex Intel Services

RexIntel Services is a crypto + AI intelligence platform built for founders, builders, researchers, and operators who need high-signal information without digging through dozens of feeds. The project combines a public intelligence directory, weekly newsletter engine, contributor system, on-chain address attribution tools, exploit tracing, recovery bounties, and an operator dashboard into one self-hosted platform. The live product is positioned as “Crypto + AI intelligence for builders,” with one weekly briefing plus live boards that the community can contribute to. At the public layer, RexIntel gives users a clean field guide for accelerators, fellowships, grants, VC capital, perks, residencies, hackathons, events, jobs, and pop-up cities. The landing page frames the brand as a crypto intelligence division that “stays deep in the trenches” so users do not have to, then routes users into Intel Wire, Field Calendar, Hackathons, Capital, Grants, Accelerators, Residencies, Pop-Up Cities, Jobs, and Perks. The core intelligence product is the /intel surface. It supports multiple lanes, including signals, accelerators, fellowships, grants, capital, perks, cities, and residencies. Individual intel records can be tips, originals, or incidents. Tips are lower-bar community sightings, originals are RexIntel-authored reporting or analysis, and incidents are confirmed exploits or failures supported by public or on-chain evidence. This taxonomy matters because the weekly digest has an editorial quality bar: it will not draft unless there is at least one original or incident unless the operator explicitly bypasses that rule. RexIntel also goes beyond a normal newsletter or directory. It includes an address graph, per-address attribution pages, an Etherscan-powered victim trace tool, and a recovery bounty board. The trace feature performs a three-hop outbound search across Ethereum activity and can create shareable trace result pages for white-hat investigators.