Top Builders

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

DeepSeek V3

General
Release date2024
AuthorDeepSeek
WebsiteDeepSeek Models
Repositoryhttps://github.com/deepseek-ai
TypeMoE (Mixture of Experts) Language Models

The DeepSeek V3 model represents our most advanced AI architecture, designed for complex reasoning tasks and code generation. With enhanced context handling and improved instruction following, this model excels in technical applications and enterprise deployments.

Key Features

  • DeepSeek-V3: 671B parameters (37B activated per token), optimized for math, code, and multilingual tasks.
  • Code Generation: Supports 12+ programming languages
  • Advanced Reasoning: Chain-of-thought capabilities for multi-step problems
  • Enterprise-Grade Security: Built-in content filtering and compliance features
  • Speed: 3x faster generation than previous versions (60 TPS)
  • Open-Source: FP8/BF16 weights available on Hugging Face

👉 Local Deployment Guide for DeepSeek V3 👉 Model Weights on Hugging Face 👉 API Documentation 👉 Deepseek V3 Paper 👉 Performance Highlights

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Deepseek DeepSeek V3 AI technology Hackathon projects

Discover innovative solutions crafted with Deepseek DeepSeek V3 AI technology, developed by our community members during our engaging hackathons.

AutoClaw - Self-Evolving Agent Economy

AutoClaw - Self-Evolving Agent Economy

AutoClaw introduces a revolutionary self-evolving agent economy where autonomous AI agents don't just execute tasks - they improve themselves. Built on OpenClaw's privacy-first runtime, our agents analyze their performance, identify weaknesses, and autonomously generate new skills using DeepSeek/Gemini AI models. The core innovation is a self-improvement cycle: agents execute tasks → analyze results → identify improvement areas → generate new code → test and deploy enhanced versions. This creates a continuously evolving system that gets smarter over time. We've integrated a complete economic layer using $SURGE tokens and the x402 protocol. Premium skills charge micro-payments (0.1-1.0 $SURGE per use) with automatic revenue sharing: 70% to skill creators, 20% to agent operators, 10% to network. This creates a sustainable ecosystem where developers earn from their skills. For hackathon compliance, our agents actively post on Moltbook (20+ posts during development) and have joined the LabLab submolt. The system features three specialized agents: Twitter Bot for social engagement, DeFi Analyzer for yield optimization, and Skill Generator that creates new capabilities. A beautiful FastAPI dashboard provides real-time monitoring of agent activity, payments, and learning progress. All data persists via SQLite memory, allowing agents to remember interactions across sessions. Built entirely open-source with MIT license, AutoClaw demonstrates what autonomous agents can achieve today while respecting user privacy through local execution.

Coffee Flow AI

Coffee Flow AI

Coffee Flow AI is an autonomous, simulation-first AI system designed to optimize coffee harvesting operations. Many coffee farms face inefficiencies due to manual decision-making, lack of real-time data, and limited automation. My solution simulates harvesting processes and applies AI-driven optimization to improve task execution, productivity, and operational efficiency. Through an interactive dashboard, I can monitor performance metrics, analyze outcomes, and make data-informed decisions. Coffee Flow AI targets coffee producers and agricultural cooperatives seeking scalable, data-driven solutions. The platform is designed to be adaptable to other crops and future integration with robotics and real-world sensors, contributing to increased sustainability and profitability in agriculture.

Warehouse Orchestrator AI

Warehouse Orchestrator AI

Warehouse Orchestrator AI is an AI-powered warehouse automation simulation platform designed to demonstrate how autonomous robots can optimize modern logistics operations. The system simulates a real warehouse environment with multiple zones (A, B, C, D, Packing, Charging Dock) where robots intelligently navigate, avoid obstacles, and complete delivery tasks. The platform includes a futuristic SaaS dashboard that provides real-time monitoring of robot status, battery levels, active tasks, performance analytics, and system logs. It showcases intelligent routing and decision-making logic that can scale to real-world warehouses. This project is built using HTML5 Canvas, JavaScript, and CSS, optimized for smooth real-time rendering, and deployed on Cloudflare Pages for fast global access. The architecture is designed to be cloud-ready and extendable for integration with Vultr infrastructure and real robotic systems.

RoboFleet AI Manager - Vultr-Powered

RoboFleet AI Manager - Vultr-Powered

RoboFleet AI Manager is a comprehensive warehouse robotics control platform built for the AI Meets Robotics Hackathon (Track 3: Task Execution). This simulation-first solution provides end-to-end management of robotic fleets through an intuitive web dashboard. **Key Features:** • **Vultr Cloud Backend**: Fully deployed on Vultr infrastructure (45.63.4.225:5000) serving as the central control system • **Warehouse Digital Twin**: Interactive 10x10 grid map showing robot positions, charging stations, and inventory shelves • **AI Command Center**: Natural language processing for robot commands with Vultr-processed AI responses • **Task Execution System**: Pick, Move, Charge functionality for autonomous robot operations • **Real-time Analytics**: Live battery monitoring, efficiency metrics, and energy savings tracking • **Mobile-Optimized Dashboard**: Responsive design working perfectly on Android/iOS devices **Technology Stack:** • **Backend**: Flask Python API deployed on Vultr Cloud Compute • **Frontend**: HTML5/CSS3/JavaScript with responsive design • **AI Integration**: Custom NLP for warehouse command processing • **Simulation**: Real-time robot behavior simulation with battery drain/charge cycles **Business Impact**: Demonstrates 40% operational cost reduction through AI optimization, scalable to 100+ robots. Perfect for warehouse logistics, manufacturing, and smart factory operations. **Hackathon Compliance**: Meets all Vultr backend requirements, Track 3 task execution focus, and provides complete simulation environment without physical hardware.

EthosAI

EthosAI

Most crypto tools focus on price charts and trading signals. Nobody tells you about *your own patterns* -- the fact that you tend to panic-swap into volatile tokens right after a dip, or that you overtrade during late-night sessions. EthosAI does that. You paste your Ethereum wallet address, and EthosAI pulls your full on-chain history from Etherscan. It looks at your transactions, token transfers, trade frequency, holding durations, and risk exposure. Then it runs that through a behavioral analyzer pipeline that identifies your dominant patterns, flags potential risk signals, and asks you reflection questions you probably haven't thought about. Want to go deeper on a specific token? Paste the contract address. EthosAI pulls market data from CoinGecko, correlates your transfer activity with price movements, and tells you things like "you tend to make large transfers right before price drops" or "your timing on this token has actually been solid." The Discord voice coach takes it further. Link your wallet to your Discord account, join a voice channel, and type `/coach`. The bot joins, listens to you talk about whatever's on your mind, and responds in real time with context from your actual wallet history. It knows your patterns. It's not generic advice, it's a conversation grounded in your real behavior. You can interrupt it mid-sentence, and it stops and listens. Everything gets persisted. Your analyses build up over time so you can see how your behavior evolves. Coaching sessions are logged with summaries, topics discussed, and nudges delivered. EthosAI is built for anyone who trades crypto and wants to understand themselves better, not get told what to buy. It's awareness, not advice.

FinContract AI

FinContract AI

FinContract AI addresses the complexities and dangers of financial trading contracts. Retail traders and small brokerage firms often face hidden risks in lengthy agreements, such as unfair liquidation rules, hidden fees, and aggressive leverage terms that can lead to significant capital loss. Additionally, navigating constantly evolving regulations across jurisdictions like the UK (FCA), UAE (SCA), Malta (MFSA), and Cyprus is challenging, resulting in non-compliance and hefty fines. High legal costs further exacerbate the issue, as hiring experts for reviews or disputes is expensive and time-consuming. Our solution is a 24/7 AI-driven platform that democratizes legal expertise. It features six powerful tools: 1) Trading Contract Risk Scanner: Detect leverage risks, fraud-prone clauses, and compliance gaps in real-time. Red flags and suggestions in seconds. 2) Generate Compliant Trading Agreements: Create compliant NDAs and client contracts for trading partners and finance ops. 3) Query Regulatory Risks: Ask: 'Is this CFD clause compliant under Malta law?' Get instant regulatory guidance. 4) Risk Trends & Predictive Suggestions: See contract risk over time with Risk Trends plus AI predictive suggestions and monitoring rules to prevent issues early. 5) Jurisdiction-Specific Trading Rules: EU MiFID, UAE SCA, FCA, CFTC, Malta – get rules and clause suggestions by region. 6) Regulatory Radar & Audit Log: Track evolving regulations, stale analyses, and every action in an audit-ready log – with one-click re-analyze when rules change. Built for accessibility, users can upload contracts via our web app for instant insights. This levels the playing field against larger institutions, making trading safer and more equitable.