Where to Store AI Agent Data?
No single database model answers every question about agent data. Match each kind to the store built for it, and give durable memory its own layer.
How autonomous agents are built, deployed, and trusted — architecture patterns, infrastructure choices, and real-world lessons across industries and frameworks.
No single database model answers every question about agent data. Match each kind to the store built for it, and give durable memory its own layer.
Agent memory
Context engineering is the design and management of information a model sees at runtime, including instructions, state, tools, retrieval, and recalled memory.
Agent memory
AI agents learn from past interactions by storing what happened and retrieving it later, not by retraining the model after every conversation.
Agent memory
AI agents store long-term memory in an external system that saves selected information outside the model, then retrieves it into the context window when it's relevant.
Agent memory
AI agents lose memory between sessions because LLM calls are stateless, where each request is processed on its own with no record of the ones before it.
Announcement
The Walrus Verifiable Trading Standard (WVTS) is the foundation agentic trading has lacked: an open standard for trading records AI agents can verify.
Product update
Carry context across apps and sessions, coordinate across agents, and own your memory. Walrus Memory plugs into AI platforms, frameworks, and your stack.
News
How Walrus grew in 2025 — Mainnet, new features, and the beta launch of Walrus Memory for AI agents.
Product update
Walrus Memory is the portable, verifiable memory layer for AI agents. Persist conversations, checkpoints, and reasoning across sessions. Now in beta.
AI agents
Autonomous DeFi agents are only as trustworthy as their data. Learn why Walrus is the verifiable, always-available data platform for agentic finance.
AI agents
Verifiable data is the missing piece in AI, advertising, and beyond.
AI agents
AI agents are moving beyond answering questions to taking real-world actions, but a critical piece remains missing: trust.