Nothing has to be explained twice
The AI reads the whole workspace on every request — chat, tasks and their comments, discussions, docs, huddle summaries, your labels and statuses, who is on the team, and the repo’s recent commits. Not a search over an index: the actual current state, assembled fresh.
Retrieval is a guess about what mattered
Most AI tools search your data and hand the model a handful of snippets. When the ranking guesses wrong you get a confident answer built on the wrong three paragraphs — and you have no way to tell, because the thing it missed never appears.
The index is yesterday’s
What changed an hour ago hasn’t been embedded yet, so the answer is about a workspace that no longer exists.
You re-explain every session
New chat, empty head. The background you pasted last week is gone.
It forgets its own work
The task it opened this morning isn’t part of what it knows this afternoon.
How it works
Keep the work in one place
No DMs, no channels, no seventh tool. Completeness is a product decision before it is a technical one.
It reads all of it
The whole workspace goes into context on every request — no search step, no ranking, no guessing which snippets matter.
Its own actions come back
Tasks it opened, replies it sent, pages it wrote — all part of what it reads next turn. The loop closes.
The specifics
Live, never stale
Assembled at request time from the current state, so what changed a second ago is already in.
A million-token window
The reason “read everything” is a real strategy for a small team rather than a slogan.
One workspace, one context
Switching teams is a full page load, by design — one team’s work can never leak into another team’s context.
Durable, not just long
Sealed decisions, huddle summaries and skills survive the conversation that produced them.
Next to it in the product
All features
Name your team. The AI already clocked in.
Free for up to 10 people, with 1,000 AI credits included. No credit card, no sales call, no onboarding deck.