This is a presentation for the Redis AI Challenge: Real-Time AI Innovators.
Project Summary
I have developed LTMC, short for Long-Term Memory and Context, a multi-agent coordination platform designed for artificial intelligence systems that require persistent memory, semantic search, and real-time orchestration. LTMC is a production-ready Model Context Protocol server that allows AI agents to collaborate while remembering everything they have done, from conversations to code snippets, across multiple sessions.
Four-Level Memory Architecture
LTMC is not just a database or a vector store. It is a memory system composed of four complementary layers: SQLite for temporary and transactional storage, FAISS for semantic vector search, Redis 8 for in-memory caching and real-time orchestration, and Neo4j for linking relationships through graphs. The combination of these technologies offers agents always-available, high-speed memory.
Key Features
Context persistence and long-term memory, efficient semantic search, real-time orchestration between AI agents, memory locking for distributed concurrency control, and replay of learned code patterns. Examples of included tools: document storage and retrieval, conversation logging, task management, knowledge graph links, and replaying learned code snippets.
Repository and Documentation
GitHub Repository: https://github.com/oldnordic/ltmc-mcp-server. Documentation and examples are included in the repository to facilitate integration and deployment.
How We Use Redis 8
Redis 8 powers two critical parts of LTMC: first, the real-time orchestration layer, which includes six specialized Redis-based services so multiple agents can collaborate without interference: agent registry to know who is online and what they are doing, context coordination for shared conversation states, memory locking for distributed concurrency control, tool caching to keep hot data always ready, shared buffers for large content, and lightweight queues for temporary synchronization. Second, Redis acts as a cache for responses under 100 ms; all hot data —context, memory fragments, tool results— passes through Redis before touching disk, ensuring very low query latencies even under load.
Performance and Scalability
On a modest server with 4 CPUs and 16 GB of RAM, LTMC can sustain hundreds of active agent sessions in real time with orchestration latencies below 100 ms. Scalability mainly depends on available CPU cores and RAM, leveraging Redis's in-memory data handling for high performance.
Use Cases
LTMC is ideal for advanced conversational support teams, enterprise assistants with long-term memory, AI agent orchestration in data pipelines, autonomous agent development platforms, and systems requiring decision auditing and traceability. It also serves as a foundation for enterprise AI solutions that require contextual persistence and continuous semantic search.
About Q2BSTUDIO
Q2BSTUDIO is a custom software and application development company specialized in artificial intelligence, cybersecurity, and AWS and Azure cloud services. We offer custom software, custom applications, business intelligence services, and AI agent implementation to solve real business challenges. Our team integrates AI solutions for enterprises, advanced analytics tools with Power BI, and secure, scalable cloud architectures.
Why Choose Us
We combine experience in custom software development with specialization in artificial intelligence and cybersecurity to deliver robust, results-oriented solutions. We implement AWS and Azure cloud services, business intelligence projects, and AI agent deployments, optimizing costs and delivery times. We integrate Power BI for advanced visualization and security layers to protect sensitive data.
Contact and Next Steps
If you need a memory and multi-agent orchestration solution, enterprise AI integration, custom application development, or consulting on AWS and Azure cloud services, contact Q2BSTUDIO for a personalized assessment. LTMC serves as an example of how we combine cutting-edge technologies to deliver custom software, applied artificial intelligence, and secure, scalable solutions.
Keywords
custom applications, custom software, artificial intelligence, cybersecurity, AWS and Azure cloud services, business intelligence services, AI for enterprises, AI agents, Power BI
