Actx0
Actx0 provides managed memory infrastructure for AI agents, allowing them to store and retrieve context across sessions with low latency.
At a Glance
- Production AI teams
- Developers building AI agents
- Enterprises using LLMs
AI Tools by Actx0
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Actx0
Managed Memory Layer for AI Agents
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Products & Services
Managed memory infrastructure for AI agents and apps that extracts facts from transcripts and retrieves them for future turns.
Official clients for Python, Node.js, and Go to integrate Actx0 memory into AI applications.
Tools to give Cursor and other MCP clients scoped memory tools for agent sessions.
Market Position
Actx0 positions itself as a drop-in infrastructure for AI memory, prioritizing low latency and managed RAG over building custom vector store pipelines. It competes with products like Mem0 and Zep.
Leadership
Founders
Ahmed Mostafa
Software Engineer and creator of Clivern; developer of multiple open-source tools including Lynx, Cattle, and Walrus; background in Petroleum Engineering.
Executive Team
Ahmed Mostafa
Founder & Software Engineer
Experienced software developer specializing in backend systems and AI-powered infrastructure.
Sanjay Ghimire
Senior AI/ML Engineer
Specialist in end-to-end AI systems, LLMs, RAG, and agentic production pipelines.
Founding Story
Actx0 was started because AI agents often suffer from 'amnesia' once a session ends, leading to redundant history and high token costs. The vision was to create a drop-in memory layer that extracts facts and persists them across users and agents.
Business Model
Revenue Model
SaaS Subscription model with multiple monthly tiers based on usage limits and support levels.
Pricing Tiers
Core workspace access, basic usage limits, community support.
Everything in Hobby plus higher usage limits and email support.
Everything in Starter plus expanded usage limits and priority capacity.
Advanced plan with highest monthly capacity and priority support.
Target Markets
- Production AI teams
- Developers building AI agents
- Enterprises using LLMs
- Customer support bots with long-term memory
- Personalized AI executive assistants
- Agentic workflows requiring cross-session persistence
- Production AI apps needing managed RAG