Redis AI technology page Top Builders

Explore the top contributors showcasing the highest number of Redis AI technology page app submissions within our community.

Redis

Redis provides access to mutable data structures such as strings, hashes, lists, sets, and sorted sets. These data structures can be manipulated using a variety of commands that are sent over a simple protocol using TCP sockets. Redis also supports various advanced features such as transactions, Lua scripting, pub/sub messaging, and bitmap operations.
The solutions from Redis provide an additional range and capabilities to solutions built on transformer technologies. RediSearch, RedisJson, and other Redis modules allow for building the next generation of AI-Native software solutions.

General
Relese date	April 10, 2009
Author	Redis
Type	in-memory data store

Tutorials

Great tutorials on how to build with Redis!

👉 Discover more Redis Tutorials on lablab.ai

Redis - Helpful Resources

Check it out to become Redis Master!

Redis Redis website
Redis Docs Documentation of Redis
Redis Repo Open-source Redis repository
Redis Cloud Redis Cloud Solution

Redis - Clients

Connect Redis to your Project!

Redis Python Client Python Client for Redis
Redis Node High-Performance Redis Client for Node.js
Redis Go Go Client for Redis
Redis Ruby Ruby Client for Redis

Redis - Boilerplates

Get started with Redis!

Redis x OpenAI - Q&A Project How to utilize Redis to build a Q&A system with OpenAI?
Paper Search App powered by Redis Speed up your research with Redis!
Redis: AI Resources List of projects/tools/ideas for using Redis with AI

Redis - Projects

ChatGPT Memory Allows to scale the ChatGPT API to multiple simultaneous sessions with infinite contextual and adaptive memory powered by GPT and Redis datastore
ChatGPT Retrieval Plugin The ChatGPT Retrieval Plugin repository provides a flexible solution for semantic search and retrieval of personal or organizational documents using natural language queries

Edit on Github

Redis AI technology page Hackathon projects

Discover innovative solutions crafted with Redis AI technology page, developed by our community members during our engaging hackathons.

Airdrop Optimizer MultiAgent System for Airdrop

📖 3. Long Description 🎯 The Problem Over US$1.2 billion in crypto airdrops go unclaimed each year. Hundreds of campaigns launch monthly, with complex requirements. Manual monitoring and execution are inefficient and unsustainable. 💡 Our Solution A multi-agent system automates campaigns in four stages: 1. Airdrop Scout Agent Simulates scraping sources (e.g., Binance). Extracts data: token, volume, reward, duration, URL. Assigns viability score (0–10). 2. Campaign Creator Agent Filters viable campaigns (score ≥ 5.0). Assigns risk (LOW / MEDIUM / HIGH). Launches Trading Agents per campaign. 3. Prediction Agent Performs technical analysis (MA, RSI), sentiment simulation, and forecasting. Produces recommendations (BUY / SELL / HOLD). 4. Trading Agent Simulates spot trades to meet volume targets. Uses stop-loss/take-profit for risk management. Tracks trades, P&L, success rate, and reports updates. 🔧 Architecture & Infrastructure Orchestrated via Celery + Redis for scalable execution. CLI entry: main.py. RESTful API with FastAPI (api/main.py) enables: Listing campaigns Starting/stopping agents Monitoring agent status Swagger UI for testing 🌐 Deployment on Vultr Hosted on Vultr SSD VPS—high-performance cloud with: Fast CPUs + SSDs for low-latency task and API performance Scalability to provision new servers for agent load and queue growth Global reach for latency-optimized deployments Cost efficiency via hourly/monthly billing Flexible deployment (Docker/K8s or direct VM) REST API exposed via load balancer for resilience 📈 Scalability & Modularity Celery allows parallel agent execution across campaigns. Each Trading Agent runs independently with unique token IDs. Simulated results include trade count, success rate, P&L, and duration.

ADHD Manager Bot

ADHD Manager Bot is a conversational productivity assistant built for Telegram, designed to support users with ADHD in managing tasks, reminders, and long-term memory — all in a friendly, casual tone. It supports both text and voice input using OpenAI’s Whisper, and replies naturally while using tools like QStash for reminders and Redis for memory. Trae IDE played a key role throughout development. Its AI code assistant offered fast, context-aware suggestions that felt remarkably accurate — far better than other tools I've used. With access to my codebase, I could iterate rapidly, fixing bugs and designing new features on the fly. I also used Trae's multi-model chat system to experiment with different LLMs inside the IDE itself, which helped shape the bot’s personality and tune the prompts for better memory usage and tone adaptation. Under the hood, the bot uses LangChain’s ZeroShotAgent architecture, enhanced with custom tools and memory, and deployed via AWS Lambda for low-cost serverless hosting. The architecture supports structured tool use while maintaining natural, assistant-like conversation flow. The bot handles casual voice messages just as well as structured commands — remembering your tone, matching your emoji use, and adjusting its responses accordingly. Overall, this project couldn’t have come together so quickly and smoothly without Trae IDE’s AI-first workflow. It enabled me to focus on solving real user problems instead of boilerplate. The result is a bot that feels more like a helpful friend than a productivity app.

Monk AI

Monk AI is a unified, intelligent developer platform that transforms the entire software development lifecycle into a seamless, single-screen experience. Designed for both solo developers and distributed teams, Monk integrates AI agents into every stage—from idea generation and coding to testing, deployment, and monitoring. The platform features an AI-powered ideation hub, a Monaco-based code editor with live autocompletion, intelligent test generation and healing, one-click deployment to cloud services, domain and SSL automation, Git versioning, observability, and real-time team collaboration. Every tab is powered by domain-specific AI agents that reduce friction and context switching. With Monk, users can start with a prompt like “Build a task manager,” and the platform will generate specs, code structure, tests, and even deploy it live—within minutes. Think of it as an AI team-in-a-box: CodeMate, GitMate, DeployMate, and more. Our hackathon MVP will demonstrate how Monk AI can generate working applications from a prompt, write tests, deploy to cloud, and monitor logs—all with minimal human input. It’s not just DevOps; it’s DevEverything.

NetConnect

Public Sector Network Connectivity Analyzer The Public Sector Network Connectivity Analyzer is a comprehensive solution designed to address the critical need for reliable network monitoring across public institutions. Our application serves as an essential tool for IT administrators managing connectivity infrastructure for schools, healthcare facilities, government offices, libraries, and other public service organizations. Core Capabilities Real-Time Network Visualization Interactive diagrams and topology maps provide clear visibility into how public institutions are connected, displaying network elements, connection points, and infrastructure components with intuitive visualization tools. Performance Monitoring System Our platform continuously tracks vital network metrics including uptime percentages, latency measurements, bandwidth utilization, and connection status across the entire public sector network, enabling proactive management. Advanced Simulation Engine IT professionals can run comprehensive simulations to test network resilience under various scenarios such as increased user loads, infrastructure failures, or cyber incidents, helping identify vulnerabilities before they impact critical services. Institution Management Portal Administrators can efficiently manage information about connected institutions, monitor their connection status in real-time, and access detailed performance metrics through a unified dashboard interface. Geographic Mapping Integration Our system incorporates geographic visualization capabilities to display the physical distribution of institutions and network infrastructure across regions, facilitating better resource allocation and planning. Technical Implementation This solution addresses the unique challenges faced by public sector organizations that require reliable connectivity for delivering essential services to communities, while providing the tools needed to ensure network resilience, performance, and security.

KNAII

KNAI transforms data analysis by addressing a critical challenge: making complex data accessible and actionable for all team members, regardless of technical expertise. Our platform leverages advanced natural language processing to create a seamless bridge between business users and their structured data repositories. Our solution is built on a sophisticated architecture powered by WatsonX and the Granite-3.1-8b-instruct model. This foundation enables KNAI to automatically understand database schemas, transforming natural language questions into precise, optimized SQL queries. The system implements intelligent filtering and maintains contextual awareness, ensuring each interaction builds upon previous queries for more meaningful insights. KNAI stands out through its comprehensive approach to data democratization. Beyond translating questions into queries, it incorporates advanced features like automatic query validation, prompt engineering optimization, and persistent conversation history. This ensures accurate results while maintaining complete transparency of the query generation process. Organizations implementing KNAI have seen substantial improvements in their data analysis capabilities, with projected metrics showing a 75% reduction in analysis time, 90% decrease in query errors, and 60% increase in decision-making speed. This efficiency translates to improved business outcomes and a projected 3x ROI in the first year. For technical teams, KNAI offers robust integration through its API, hosted on IBM Code Engine, with PostgreSQL for structured storage and Redis for conversation management. For business users, it provides an intuitive interface that makes complex data analysis as simple as having a conversation. By eliminating traditional barriers between business users and their data, KNAI enables organizations to make more informed decisions faster, unlock hidden insights, and drive innovation across all levels.

3D Virtual Assistant AI for Astronauts

An advanced AI-powered 3D virtual assistant designed to assist astronauts during space missions with real-time voice interaction, facial animations, and intelligent responses.3D Realistic Human Assistant: Built using Three.js and Blender models for lifelike animations and interactions. Real-time Speech Recognition: Converts astronaut commands into text using advanced AI models like OpenAI Whisper. LLM-Powered Conversation: Provides intelligent and context-aware responses using OpenAI, LLaMA, and Custom GPT. Text-to-Speech (TTS) Synthesis: Generates lifelike voice responses using Google TTS, Amazon Polly, and OpenAI TTS. Lip Sync & Facial Animations: Enhances realism using Viseme-based animation techniques. Multi-Platform Support: Compatible with web (React), desktop (Unity), and mobile (React Native) platforms.Mission Integration: Offers real-time mission status updates and alerts, making it a valuable tool for space missions. The project targets space agencies, aerospace companies, AI technology firms, and research institutions, providing enhanced astronaut support, improving mission efficiency and safety, and creating new opportunities for innovation in AI and space technologies.