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Memory.Inc remembers your team's scattered work context across docs, messages, email, and AI chats, then helps AI agents work and take action the way your team does. It learns decisions, workflows, preferences, and operating rules, finds the right context by meaning, relationships, and time, and turns it into practical next steps: drafting replies, preparing updates, routing tasks, and supporting workflows in the tools your team already uses.
We built Memory.Inc around a simple belief: AI should not just answer questions. It should understand how your team works, then help get real work done.
Today, teams use ChatGPT, Claude, Claude Code, Cursor, and other AI tools every day. But every session still starts from zero. You have to re-explain the product, decisions, customer history, project rules, coding conventions, Slack context, Linear tasks, GitHub discussions, and all the small “this is how we do it here” details.
Memory.Inc remembers that scattered work context across docs, messages, email, and AI chats, then gives AI agents the right background to act in your team’s way. The goal is not to store everything or dump a giant knowledge base into the prompt. The goal is to help AI understand your team’s decisions, workflows, preferences, operating rules, and tools so it can take useful next steps.
That might mean drafting the right reply, preparing a project update, finding the relevant decision, routing a task, or supporting a workflow in the tools your team already uses. Useful decisions and repeated workflows become clearer over time, while outdated context becomes less prominent.
Our long-term vision is a Company Brain for AI agents: one place where your team’s way of working is remembered and turned into useful action across your tools.
We’d love your feedback: where do your AI tools most often fail because they don’t understand your team’s context or the action they should take next?
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About Memory.Inc on Product Hunt
“Make AI agents work like your team”
Memory.Inc was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #134 on the daily leaderboard. Memory.Inc remembers your team's scattered work context across docs, messages, email, and AI chats, then helps AI agents work and take action the way your team does. It learns decisions, workflows, preferences, and operating rules, finds the right context by meaning, relationships, and time, and turns it into practical next steps: drafting replies, preparing updates, routing tasks, and supporting workflows in the tools your team already uses.
Memory.Inc was featured in Productivity (655.6k followers) on Product Hunt. Together, these topics include over 144.6k products, making this a competitive space to launch in.
Who hunted Memory.Inc?
Memory.Inc was hunted by Leo Jang. 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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Leo Jang
Hey Product Hunt, I’m Leo, founder of Memory.Inc.
We built Memory.Inc around a simple belief: AI should not just answer questions. It should understand how your team works, then help get real work done.
Today, teams use ChatGPT, Claude, Claude Code, Cursor, and other AI tools every day. But every session still starts from zero. You have to re-explain the product, decisions, customer history, project rules, coding conventions, Slack context, Linear tasks, GitHub discussions, and all the small “this is how we do it here” details.
Memory.Inc remembers that scattered work context across docs, messages, email, and AI chats, then gives AI agents the right background to act in your team’s way. The goal is not to store everything or dump a giant knowledge base into the prompt. The goal is to help AI understand your team’s decisions, workflows, preferences, operating rules, and tools so it can take useful next steps.
That might mean drafting the right reply, preparing a project update, finding the relevant decision, routing a task, or supporting a workflow in the tools your team already uses. Useful decisions and repeated workflows become clearer over time, while outdated context becomes less prominent.
Our long-term vision is a Company Brain for AI agents: one place where your team’s way of working is remembered and turned into useful action across your tools.
We’d love your feedback: where do your AI tools most often fail because they don’t understand your team’s context or the action they should take next?