IJONIS Logo
IJONIS
Agentic AI

Memory Management

Memory Management in Agentic AI describes the techniques by which AI agents store, retrieve, and prioritize information beyond individual interactions. It encompasses short-term memory (conversation context), long-term memory (learned knowledge), and episodic memory (experiences from past tasks).

Why does this matter?

Without memory, an AI agent must start every task from scratch. With intelligent memory management, the agent learns from past interactions: it knows your preferred suppliers, which approval steps are needed, and remembers previous decisions. This saves onboarding time on every invocation.

How IJONIS uses this

We implement three-tier memory with Redis for short-term context, pgvector/Pinecone for semantic long-term memory, and structured databases for episodic memory. LangGraph checkpointing preserves state in long-running workflows — no context is lost even after system restarts.

Frequently Asked Questions

Is the long-term memory of an AI agent GDPR-compliant?
Yes, when properly implemented. We store personal data only in your own infrastructure (on-premise or EU cloud), implement automatic deletion periods, and granular access controls. Every memory entry is assigned to a data owner and can be selectively deleted.
How much context can an AI agent process simultaneously?
The context window of modern LLMs spans 128,000 to 2 million tokens. Through intelligent memory management, the agent selectively retrieves the most relevant information — rather than filling the context window randomly. This keeps response quality consistently high even with large knowledge bases.
← Back to Glossary

Want to learn more?

Find out how we apply this technology for your business.

Start AI Readiness Check