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Build stateful AI agents

Bio-inspired model: DNA memory layer, RNA memory regulation layer, Protein context assembly

Join Waitlist Experience the 3-Layer Model

Built for MCP servers and long-running AI agents that need reliable memory, lower token waste, and stable performance over time.

Lower token waste o Cleaner context at inference time o Model agnostic memory control

Why teams switch

Beyond store-and-retrieve memory

Most systems dump everything into retrieval and hope it works. smarna actively regulates memory so long-running agents stay coherent. 

session.add(message)session.learn()session.get_context(token_budget=10000)

THE MODEL

01 DNA memory layer

Durable source of truth for complete interaction history.

02 RNA regulation layer

Reasoning layer that scores, compresses, and prioritizes context.

03 Protein context control layer

Final context assembly injected into the LLM at runtime.