Unabyss for Claude

openclaw alternative??

This new version looks cool. How does permission layer works? Can I give access to my context to someone else?

Following this one because I trust the team behind it. Genuine question for anyone who's set it up: how deep does the context actually go on day one vs. after a week of syncing? That's the part I'd want to see before I move my whole stack over. Either way, congrats on the relaunch 🎉

The portable memory angle is the strongest part of this. One thing I haven't seen addressed though ,what happens when you disconnect a source? If I connected Notion six months ago and Unabyss built context from it, then I disconnect Notion or delete those docs, does that memory get cleaned up automatically or does stale context from a deleted source keep surfacing in other tools indefinitely?

Congrats on your relaunch!! Have you seen more adoption from individual power users or teams?

How do you handle data consistency and integrity across different AI tools and apps connected through Unabyss, especially when updates are made to the context layer?

I run a hand-rolled version of this for a fleet of Claude agents — plain files, one fact per file — and the failure mode that taught me the most wasn't retrieval, it was propagation: one agent writes a fact that's slightly wrong or goes stale, and every other agent confidently inherits it. So my question is about contradictions: when a fresh observation from Gmail disagrees with an old memory that came from Notion, does the old one get overwritten, versioned, or decayed? And can I audit which app wrote a given memory? Provenance is the part I'd actually pay for.

Good luck with the launch you guys

Finally something that fixes the “let me paste my whole life story into the prompt again” problem. Hooked it up to my notes and Gmail, and Claude actually remembered my project context without me retyping anything.

shared memory across apps and models is the thing I actually want, I context-switch between 3 different assistants all day and lose the thread every time. how do you handle memory conflicts when two apps write contradicting facts about the same thing

The landing page UI alone made me want to try it - super smooth, intuitive, and instantly communicates what the product is about. Congrats on the launch!

The hard part with shared memory is not storage, it is correction. If a bad fact gets extracted from Slack or an old doc, teams need to see source, freshness, confidence, and the exact downstream places that may now be wrong. That audit trail is what makes portable context usable for real work.

Sheesh! It's so coolIt genuinely solves one of the biggest frustrations with ai today, ie having to rebuild context every time you switch tools if it works! Will def try this out and give my feedback

Congrats on the launch! The retrieval-time conflict resolution looks to be the crucial part? A lot of memory layers just dump everything into context and let the model referee - but you look to be on the right path. QQ - recency as the tiebreaker assumes newer means truer, but a stable preference from 3 months back usually beats something I typed once yesterday in a bad mood right? How do you guys tell a durable fact from a throwaway one when the two collide?

congrats on the relaunch, curious how context conflicts are handled when the same topic shows up differently across integrations like notion vs hubspot vs slack.