Every agent builder I’ve spoken with hits the same wall: their agents execute a task perfectly, but completely forget the context the next time they run. Vector stores are the standard workaround, but they get messy, are difficult to debug, and don't function as true memory. We designed Antonlytics to solve this cleanly: • 5-minute integration: Add three lines of code (or a single REST call) to give your agent persistent, structured memory. It works out of the box with LangChain, CrewAI, LangGraph, or any custom stack. No vectors to manage and no schemas to maintain. • Automated knowledge graphs: It automatically structures conversations into a clean graph of people, companies, events, and relationships so your agent can query it naturally. We use this as the backbone for our own app, Slatt. It allows Slatt to function as a collective intelligence agent that gets smarter by learning from every single conversation.

Antonlytics

Structured memory for AI agents that never forget

Structured memory for AI agents that never forget