This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
MCIS
The memory-first AI for thinking, learning, and building
MCIS (Memory-Centric Intelligence System) is an AI assistant designed to remember what matters. Unlike traditional AI chats that lose context over time, MCIS uses persistent memory to help users continue conversations and projects across sessions. It offers personalized interactions, context-aware responses, intelligent memory retrieval, and an organized workspace, making AI more useful for long-term learning and productivity.
Hi Product Hunt! 👋
I'm Ananya, the creator of MCIS.
I built MCIS because I was frustrated that most AI assistants forget previous conversations, forcing users to repeat context again and again.
MCIS is designed with persistent memory so conversations can continue naturally across sessions. My goal is to make AI feel more like a long-term collaborator instead of a temporary chatbot.
This is an early version, and I'm actively improving it based on user feedback.
I'd genuinely love to hear:
• What feature do you find most useful?
• What would make you switch to an AI assistant with long-term memory?
• What should I improve next?
Thank you for checking out MCIS! 🙌
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About MCIS on Product Hunt
“The memory-first AI for thinking, learning, and building”
MCIS was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #121 on the daily leaderboard. MCIS (Memory-Centric Intelligence System) is an AI assistant designed to remember what matters. Unlike traditional AI chats that lose context over time, MCIS uses persistent memory to help users continue conversations and projects across sessions. It offers personalized interactions, context-aware responses, intelligent memory retrieval, and an organized workspace, making AI more useful for long-term learning and productivity.
MCIS was featured in Productivity (656.6k followers), Artificial Intelligence (474.1k followers) and Tech (628.3k followers) on Product Hunt. Together, these topics include over 421.9k products, making this a competitive space to launch in.
Who hunted MCIS?
MCIS was hunted by Ananya Jindal. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Ananya Jindal