Persistent Memory for AI Agents (Finally) | Introducing Cognis

Your AI agent doesn’t have a memory problem. It has a forgetting problem. Every time a session ends, your agent resets. It forgets who you are. What you said. What matters. That’s why AI feels inconsistent. In this video, we introduce Cognis, Lyzr’s memory layer for AI agents. With just a few lines of code, your agent can: extract facts from conversations update memory over time avoid contradictions and retrieve relevant context across sessions No vector database setup. No complex infrastructure. Just memory that actually works. Because real AI systems don’t just respond. They remember. ⏱️ Chapters 0:00 The real problem: AI forgets everything 0:06 Introducing Cognis (memory layer) 0:12 Why most agents lose context 0:21 Installing Cognis (simple setup) 0:33 API keys and configuration 0:50 Creating a memory instance 1:03 How memory extraction works 1:23 Automatic fact extraction from conversations 1:40 Categorizing memory (identity, work, interests) 1:54 Updating memory without conflicts 2:14 How Cognis replaces outdated facts 2:39 Searching memory effectively 2:50 Hybrid search explained 3:23 Using “get context” in agents 3:39 Combining short-term + long-term memory 3:55 Session vs persistent memory 4:08 Memory across sessions 4:18 Multi-agent memory separation 4:29 Final recap 🔗 Important Links: Build with Architect: https://hubs.ly/Q043pWTs0 Build your own AI agent → https://hubs.ly/Q03wb5Md0 Explore our website → https://hubs.ly/Q03wbGVt0 Build agents for your company (Book a demo) → https://hubs.ly/Q03wbH0k0 Learn how to build agents with Lyzr Academy → https://hubs.ly/Q03wqxFR0