Product Positioning & Context
Atlaso is a memory layer for AI. Connect it once and every AI you use, from Claude Code to Cursor, Codex and ChatGPT, automatically recalls the context that matters: your projects, your decisions, and the way you like to work. No more re-explaining yourself at the start of every session. One shared memory that follows you across every tool, instead of being locked inside one app. Free to start, and backed by original memory research.
Related Ecosystem & Alternatives
Discover adjacent products, open-source repositories, and developer tools sharing similar technical architecture.
Deep-Dive FAQs
What is Atlaso?
Atlaso is a digital product or tool described as: One memory for every AI you use
Where did Atlaso originate?
Data for Atlaso was aggregated directly from the Product Hunt community ecosystem, representing raw developer and early-adopter sentiment.
When was Atlaso publicly launched?
The initial public indexing or launch date for Atlaso within our tracked developer communities was recorded on August 4, 2026.
How popular is Atlaso?
Atlaso has achieved measurable traction, logging over 205 traction score and facilitating 25 recorded discussions or engagements.
Which technical categories define Atlaso?
Based on metadata extraction, Atlaso is categorized under topics such as: Productivity, Developer Tools, Artificial Intelligence.
How does the creator describe Atlaso?
The original author or development team describes the product as follows: "Atlaso is a memory layer for AI. Connect it once and every AI you use, from Claude Code to Cursor, Codex and ChatGPT, automatically recalls the context that matters: your projects, your decisions, ..."
Community Voice & Feedback
This is awesome, bouncing between all of my AI platforms and pulling context across them is a big pain. Congrats on the launch!
Congrats on the launch Ashish, and the way you’re answering people here is genuinely refreshing. Publishing the benchmark you lose on is not a small thing.
My question comes from outside the dev lane. Memory is scoped global and per project, which is right for one person, but at our company half the context worth remembering belongs to the team, not to me. Brand rules, who owns what, decisions we made and why. Today if I correct something, my AI knows it and my colleague’s still gets the old version. Is a shared team memory layer on the roadmap, with the same supersede logic applied across people rather than tools? That’s the version I could roll out to 36 people instead of just using myself.
My question comes from outside the dev lane. Memory is scoped global and per project, which is right for one person, but at our company half the context worth remembering belongs to the team, not to me. Brand rules, who owns what, decisions we made and why. Today if I correct something, my AI knows it and my colleague’s still gets the old version. Is a shared team memory layer on the roadmap, with the same supersede logic applied across people rather than tools? That’s the version I could roll out to 36 people instead of just using myself.
The re-explaining tax is real, I switch between Claude Code and other tools daily and re-establishing context every time is the part nobody talks about when they compare AI coding tools. Curious how you handle the per-project vs global split when two projects share similar tech but different conventions.
Does memory compile and bulge the memory file or is there a natural decay built in?
I've built a version of this by hand for a single tool — a memory file with explicit ownership rules so every fact lives in exactly one place, plus an archive for anything superseded. It works, but only because I maintain it myself. Two questions from the maintenance end:Tidy-up. Mine stays usable because I prune it, and because there's a rule that a new fact contradicting an old one gets flagged to me rather than silently overwriting. As Atlaso's store grows across four tools and hundreds of sessions, what happens when session 40 contradicts session 4 — overwrite, version, or surface the conflict? And does anything decide a memory has gone stale, or does it accumulate forever?Token cost. If memory is injected into every session, my bill scales with how much I've remembered. Is it selective retrieval or the whole store? Roughly what's the per-session overhead at 500 memories versus 50?
"It orients, it never invents" is the claim I'd want stress tested, and not against a benchmark you ran yourself. The hard case for auto capture isn't invention, it's a decision you reversed three sessions ago still getting injected as settled, and it reads exactly as confident as a correct one. So the real question is how a memory dies. If I can't see what got injected and kill it in one keystroke, I'll turn the whole thing off the first time it confidently reminds me of the wrong thing.
Congrats on the launch!
What sets Atlaso apart from Supermemory, which I'm currently using? Especially interested in how you handle developer-focused workflows across tools like Claude Code and Cursor.
Also, is there an easy way to import or sync existing memory from Supermemory, or do we need to start from a clean slate?
What sets Atlaso apart from Supermemory, which I'm currently using? Especially interested in how you handle developer-focused workflows across tools like Claude Code and Cursor.
Also, is there an easy way to import or sync existing memory from Supermemory, or do we need to start from a clean slate?
Atlaso started as a question I couldn't shake: what would it actually take to give AI a real memory?
Not a bigger context window. Not a notes file stapled onto the side. A real memory foundation layer — one that persists, stays honest, and actually helps across sessions and tools.
That question turned into research. We ran our own memory benchmarks, and our approach held up better than the other memory systems we tested against. A lot of the work was in the unglamorous parts: what should be saved, what should be surfaced, and how to make sure memory orients you instead of quietly making things up.
The reason I cared so much is simple — I was tired of re-explaining myself to every AI I used. I'd tell Claude Code about a project, switch to Cursor, and start over. Then again in Codex. Same context, same decisions, same preferences, over and over.
Atlaso is what came out of that work: one memory layer for the AI tools you already use. Connect it once and your context follows you — global memory for what travels with you, per-project memory for what should stay separate.
My favorite part is Ambient Memory — what we call giving AI a subconscious. Before you type a word, Atlaso surfaces a short orientation from your own memory, so the AI picks up where you actually left off. It orients, it never invents.
It's free to start. I'm Ashish, the founder — I'll be in the comments all day, and I'd genuinely love your feedback: what would make AI memory actually useful to you?
Not a bigger context window. Not a notes file stapled onto the side. A real memory foundation layer — one that persists, stays honest, and actually helps across sessions and tools.
That question turned into research. We ran our own memory benchmarks, and our approach held up better than the other memory systems we tested against. A lot of the work was in the unglamorous parts: what should be saved, what should be surfaced, and how to make sure memory orients you instead of quietly making things up.
The reason I cared so much is simple — I was tired of re-explaining myself to every AI I used. I'd tell Claude Code about a project, switch to Cursor, and start over. Then again in Codex. Same context, same decisions, same preferences, over and over.
Atlaso is what came out of that work: one memory layer for the AI tools you already use. Connect it once and your context follows you — global memory for what travels with you, per-project memory for what should stay separate.
My favorite part is Ambient Memory — what we call giving AI a subconscious. Before you type a word, Atlaso surfaces a short orientation from your own memory, so the AI picks up where you actually left off. It orients, it never invents.
It's free to start. I'm Ashish, the founder — I'll be in the comments all day, and I'd genuinely love your feedback: what would make AI memory actually useful to you?
Discovery Source
Product Hunt Aggregated via automated community intelligence tracking.
Tech Stack Dependencies
No direct open-source NPM package mentions detected in the product documentation.
Media Tractions & Mentions
No mainstream media stories specifically mentioning this product name have been intercepted yet.
Deep Research & Science
No direct peer-reviewed scientific literature matched with this product's architecture.
SaaS Metrics