CloudThinker

Autonomous Cloud Operations. Unified.

35 followers

Autonomous Cloud Operations. Unified.

35 followers

AI agents that manage your infrastructure, review code, resolve incidents, and optimize costs — across multi-clouds, Kubernetes, and everything in between.

This is the 3rd launch from CloudThinker. View more

MemGraph by CloudThinker

Launching today

Long-term knowledge graph memory for AI cloud agents.

Introducing MemGraph — Long-Term Memory for AI Cloud Agents Your AI agent brilliantly diagnosed a connection storm last Tuesday. On Wednesday, the exact same pattern appeared — and the agent started from zero. This is the story of MemGraph: a knowledge graph memory system that lets AI agents remember, connect, and evolve operational knowledge across every conversation.

Free Options

Launch tags:Artificial Intelligence•Tech

Launch Team / Built With

XHawk 0.99 — Transform Coding Sessions into Knowledge

Transform Coding Sessions into Knowledge

Promoted

Maker

📌

👋 Hi Product Hunt! I'm Steve, Founder at CloudThinker. We are so excited to introduce MemGraph today! 🚀 The Problem: > We’ve been building and using AI agents for cloud operations, and we kept hitting a wall: AI agents are basically goldfishes. 🐠 They brilliantly diagnose a server issue on Tuesday, but when the exact same issue happens on Wednesday, they start from zero. We tried standard RAG (Vector databases), but it acts like a dumb filing cabinet. If a procedure is updated, the agent just blindly retrieves both the old and new docs. It has no concept of what knowledge is outdated, what is a prerequisite, or what has actually worked in production. The Solution: Enter MemGraph. We rebuilt agent memory as a Knowledge Graph. 🧠 Instead of isolated text chunks, MemGraph treats operational knowledge as connected nodes. Every time your agent solves a problem, MemGraph extracts the methodology, evolves it, and connects it to what it already knows. ✨ What makes MemGraph different? 🔗 Relationships, not just vectors: It understands that "VPC peering" is a prerequisite for another task, or that a new gp3 migration guide supersedes the old gp2 one. 🔄 The Evolution Pipeline: It doesn't just hoard data. It actively combines related memories and discards duplicates after every conversation. 📈 Earned Trust: Procedures that successfully fix issues get a confidence boost. Outdated ones get deprecated. ⚡ 8-Second Resolutions: What used to take a 12-minute diagnosis from scratch now takes seconds because the agent remembers the exact fix from your last P1 incident. Whether you're tired of re-explaining your team's Terraform preferences to your AI, or you want your agents to actually learn from past outages, MemGraph compounds your team's engineering knowledge on autopilot. We’d love for you to check it out! Let us know what you think in the comments—how are you currently handling memory and context for your AI workflows? I'll be here all day answering your questions! 👇

Report

15h ago

As someone who runs AI agents in production, this hits home hard. An agent that brilliantly diagnoses a connection storm on Tuesday and starts from zero on Wednesday isn’t just annoying — it’s operationally dangerous. Knowledge graph memory with entity relationships is exactly the right primitive here, not just flat embeddings. Excited to see how MemGraph handles schema evolution over time. Upvoted!

Report

5h ago

Previous CloudThinker Launches

CloudThinkerNow you can "vibe-operate" your multi-cloud environments.

Launched on October 15th, 2025

CloudThinkerAI Agents for Cloud Productivity, Operation and Optimization

Launched on June 23rd, 2025