I built AgentKeeper to solve a fundamental problem with AI agents: memory persistence.

Today, agents lose memory when:

• switching providers • restarting • crashing

AgentKeeper introduces a cognitive persistence layer that stores facts independently of any LLM provider and reconstructs context dynamically.

It works across:

• OpenAI • Anthropic • Gemini • Ollama

Memory survives provider switches and restarts.

GitHub: https://github.com/Thinklanceai/agentkeeper

I'm curious if others have faced the same problem and how you're handling memory persistence today.