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.