Unabyss for Claude

Shared memory across all apps and LLMs. In Claude

Productivity

Artificial Intelligence

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Portable context across tools is important. The hard problem seems to begin when those tools create conflicting memories or interpretations. How does Unabyss decide which context remains authoritative when Claude, GPT, and Cursor update the same subject differently?

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.

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.

Hey, congrats on the launch! I’ve been following the AI memory space for a while, so I’m curious how you see Unabyss alongside tools like Mem0, Zep, Cognee, and claude-mem.

What feels like the biggest difference to you today?

I’m especially interested in how you approach conflicting or outdated memories when several apps and agents contribute to the same context. It seems like one of the hardest and most interesting problems in this space.

P.S. Saw you followed me on linkedin. Thumbs up and followed!

Would love to see a quick preview of exactly what context each AI tool will receive before sharing, like a diff view so I can tweak it without digging through settings every time.

Your pitch sounds compelling, but what's the actual technical moat compared to existing MCP servers, RAG pipelines, and personal knowledge systems? For example, I can already connect Claude/GPT to Gmail, Google Drive, GitHub, Notion, Slack, and meeting transcripts using OpenMemory, Mem0, Zep, Graphlit, LangChain/LlamaIndex, or even custom MCP servers. Beyond packaging and UX, what is genuinely difficult to replicate? Why couldn't a competent engineer build an equivalent system in 7–14 days using existing APIs and open-source infrastructure?
How do you resolve conflicting memories across different sources?

How do you decide what deserves to become a long-term memory versus transient context?

Is your advantage primarily data ingestion, memory consolidation, retrieval quality, or simply convenience?

One more question: doesn't your business model create a "double payment" problem? Users already pay subscriptions for GPT, Claude, or Cursor. If Unabyss sits in the middle and consumes additional tokens to build and maintain shared memory, doesn't that mean users end up paying twice for essentially the same AI stack? How do you address that concern?

Congrats on the second launch, Philip and team! I’ve definitely burned way too many tokens re-explaining the same product, preferences, and project context every time I move between Claude, Cursor, and ChatGPT, so this immediately feels useful.

The only thing I’d worry about is context getting bloated over time. Would love a simple way to see exactly what memory is being pulled in, how many tokens it uses, and quickly pin, trim, or exclude certain context before it gets passed to another tool.

The MCP-first approach is the right call, and I like that conflicts get flagged to the user instead of the system silently picking one source over another. Most memory tools quietly decide what's true about you, this one at least asks.

One thing I didn't see addressed yet in the thread, when context gets pulled from something like Slack or Gmail that includes other people's names and info alongside yours, is there any filtering to keep that out of your personal vault, or does the extraction just take whatever's in the source as-is.

@malpunek Congratulations. And happy product launch.

Epic! Looking forward to trying this out.

Congrats on the launch 🚀

Legit ran into this issue when Launch QA time came up. Lots of missing pieces where I had to hunt down Product.md to double check items. This looks slick.