Inkfold
Shared context and memory across your AI tools
I've been building Inkfold solo to fix something that bugs me daily: working across multiple AI tools means my context is fragmented. Every provider is its own silo with its own memory, so I'm constantly re-explaining myself and copy-pasting between GPT, Claude, and Gemini.
Inkfold is one workspace that sits across providers and keeps shared context and history between them — plus FinOps-style analytics so you can actually see cost and usage across models in one place.
Where it's at: desktop is solid, mobile web is rougher, and some dev-workflow integrations (CLI/daemon) are still stabilizing. Genuinely early — I'm opening a small alpha and looking for a few developers and AI power users to break it and tell me what's confusing.
Question for other builders here: how are you currently handling context fragmentation across AI tools? Curious whether people just live with the copy-paste, or have their own workarounds — it'd help me know what to prioritize.
If you juggle multiple AI tools and want in, comment and I'll follow up.
1 Comment
I wonder if the real competitor isn't GPT, Claude, or Gemini.
It's the growing pile of context people keep in their heads because moving it between tools is so expensive. If Inkfold becomes the place where that context lives, the choice of model becomes much less important than the continuity of the workspace.