# Walrus launches Memory layer for AI agents, enabling portable

**Published:** 2026-06-13T14:07:59.608Z  
**Topic:** OpenGradient  
**Sentiment:** neutral  
**Publisher:** TrendWatcher — https://www.trendwatcher.in/article/0770e042-fba1-4a5e-b2d1-e9a7d35b9dd8

Walrus introduces MemWal SDK and Walrus Memory, a decentralized, encrypted memory layer for AI agents that offers portability, verifiability, and multi‑agent

Walrus, the decentralized storage protocol built on the Sui blockchain, has unveiled a new memory layer for AI agents that stores encrypted data on its network and adds semantic search capabilities, allowing agents to retrieve context by meaning rather than exact keywords [1].

**Key takeaways**
- The MemWal SDK provides a “remember” and “recall” API for agents to store and query encrypted memories on Walrus’s decentralized infrastructure [1].  
- Walrus Memory is marketed as portable, verifiable and user‑controlled, with default encryption and programmable access permissions [4].  
- Integrations include major models such as Claude, ChatGPT and Gemini, plus plugins for OpenClaw and NemoClaw frameworks [3].  
- The platform claims to improve retrieval relevance through ranking, filtering and cryptographic verification, reporting up to 60 % better results in internal tests [3].  
- The SDK is currently in beta and ships with Vercel AI SDK support, documentation and a GitHub feedback channel [1].

## Decentralized memory for AI agents

Walrus’s MemWal SDK is designed to give AI agents a persistent memory that lives on a verifiable data layer rather than on a single provider’s servers. The Sui blockchain handles ownership and access control, meaning users decide who can read, write or share an agent’s memories [1]. The SDK stores encrypted memories on the Walrus network and layers a semantic‑search retrieval system on top, enabling agents to query their own memory intelligently based on meaning [1].

The product is positioned as a solution to what Mystic Labs co‑founder Kostas Chalkias calls the “real bottleneck” in AI—agentic memory. Chalkias argues that current workflows force developers to stitch together databases, vector stores and runtime state, leading to unreliable agents that forget context [3]. Walrus Memory aims to address this by offering four pillars: verifiability, availability, portability and shareability. Verifiability is provided through cryptographic tools such as zk‑proofs that let agents confirm data integrity; availability is ensured by the decentralized network; portability allows memories to move between models and vendors; and shareability enables multiple agents to collaborate using shared memory pools [1][4].

## Integration ecosystem and early adoption

The launch includes direct support for leading AI models—Claude, ChatGPT and Gemini—and plugins for the OpenClaw and NemoClaw agentic frameworks, as well as Python and TypeScript SDKs [3][4]. Additional integrations with the Vercel AI SDK and quick‑start guides are part of the beta release, and the team is gathering developer feedback via GitHub [1]. Early adopters such as Allium, Conso Labs, Inflectiv, OpenGradient, Talus Labs and Tatum are already experimenting with the platform to build portable agent identity systems and assistants that retain customer interactions across sessions [3].

## Why it matters

Walrus Memory represents one of the first attempts to provide a blockchain‑backed, portable memory layer specifically for AI agents. By moving memory off proprietary platforms and into a decentralized, encrypted store, the solution promises greater user control, cross‑model compatibility and improved retrieval quality. If the claimed 60 % improvement in ranking and filtering holds in broader deployments, developers could see faster, more reliable agent workflows and reduced engineering overhead for custom storage solutions. The beta launch and growing ecosystem suggest that the next few months will be critical for testing scalability, enterprise readiness, and the ability to meet evolving privacy and compliance requirements.

## Sources
1. KuCoin — [Walrus Launches MemWal SDK for AI Agents with... | KuCoin](https://www.kucoin.com/news/flash/walrus-launches-memwal-sdk-for-ai-agents-with-verifiable-portable-memory)
2. Completeaitraining — [Walrus Memory | Complete AI Training](https://completeaitraining.com/ai-tools/walrus-memory/)
3. Decrypt — [Walrus Memory Enables AI Agents to ‘Actually Learn About Us’: Mysten Labs Co-Founder](https://decrypt.co/369895/walrus-memory-enables-ai-agents-to-actually-learn-about-us-mysten-labs-co-founder)
4. TMCnet — [Walrus Launches Walrus Memory as Portable Memory Layer for AI Agents](https://www.tmcnet.com/usubmit/2026/06/03/10393997.htm)

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Cite as: TrendWatcher, "Walrus launches Memory layer for AI agents, enabling portable", https://www.trendwatcher.in/article/0770e042-fba1-4a5e-b2d1-e9a7d35b9dd8