Murmell

Google docs for AI agents, and you can close your laptop

Developer ToolsTech

▲ 77 votes8 commentsLaunched Sep 1, 2026

Daily #9Weekly #28

Our first Product Hunt launch brought many new users to Murmell and showed us that the infrastructure was not ready to scale. So we rebuilt it from scratch. We also created unified agent memory: close your laptop, freeze a canvas, and return to the exact same workspace, terminals, files and conversations. Your agents retain their context and continue where they stopped, while teammates can join the same live environment and collaborate in real time.

AI Analysis

📝 Summary

Murmell is 'Google Docs for AI agents', providing a persistent collaborative workspace. Core features include unified agent memory, the ability to close your laptop and return to the exact same canvas with terminals, files, and conversations, plus real-time teammate collaboration. It solves infrastructure scaling issues exposed during Product Hunt launch and the pain of agents losing context. The value proposition is an always-on, freezeable environment where AI agents continue independently and teams collaborate seamlessly without losing progress.

📈 Market Timing

In 2025-2026, the AI agent space is experiencing rapid growth with trends toward autonomous, multi-agent systems and demand for better memory management and orchestration tools. Technology for LLMs and real-time collaboration has matured, user needs for persistent AI workflows are rising, and the economic environment favors AI productivity tools. This aligns perfectly with current demands. Excellent Timing.

✅ Feasibility

Technical difficulty is significant for maintaining persistent agent states, real-time sync, and scalable infrastructure, as evidenced by the initial launch issues. However, the team successfully rebuilt from scratch, indicating good execution. Operational costs for always-on environments may be high, but cloud scalability is strong with low apparent compliance risks. Overall rating: High.

🎯 Target Market

Main target segments: AI developers, software engineers, and tech teams building multi-agent systems (demographics: tech professionals aged 25-40). Industries: AI/software development, startups. Geographic: primarily US and Europe. AI developer tools TAM exceeds $15B, with SAM for agent platforms ~$2B. Core pain points are context loss and collaboration barriers. High willingness to pay for productivity-enhancing SaaS.

⚔️ Competition

Competition level: Medium. Direct competitors: 1. CrewAI (crewai.com), 2. LangGraph (langchain.com/langgraph), 3. AutoGen (microsoft.github.io/autogen), 4. E2B (e2b.dev). Advantages: superior persistent memory, 'close laptop' resumption, and Google Docs-like real-time collaboration not deeply integrated in others. Disadvantages: newer entrant with less mature ecosystem and potentially higher operational complexity than framework-focused competitors.

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