AI Assistant
Multi-channel conversational AI with persistent memory and voice interface
The Challenge
Most AI assistants are stateless — they forget everything between conversations. Building a truly useful assistant requires persistent memory, voice interaction, and the ability to operate across multiple channels simultaneously.
Our Approach
Implemented a graph-based memory system using Neo4j and Graphiti that stores relationships between entities, conversations, and learned preferences. Added real-time voice via Deepgram and ElevenLabs, with multi-channel deployment.
The Solution
The AI Assistant remembers past conversations, user preferences, and entity relationships through its graph memory system. It can operate across web, Discord, and Slack with real-time voice interaction, acting as a persistent, context-aware agent.
Key Results
- Graph-based memory system using Neo4j and Graphiti for persistent context
- Real-time voice interface powered by Deepgram and ElevenLabs
- Multi-channel deployment across web, Discord, and Slack
- Modular agent architecture supporting tool use and multi-step reasoning
- WorkOS authentication supporting up to 1M MAU