Chats
How AccessLayer turns connected data into grounded chat answers.
Chats are the conversational layer on top of AccessLayer's connector-backed data model. They are where you explore, iterate, and pressure-test a question before deciding whether it should become something more permanent.
Private to you
Chats belong to your user account. Even if multiple people are in the same organization, they cannot see your chats. This is different from dashboards, which are shared across the organization.
What chats depend on
Every chat depends on the same foundation as the rest of AccessLayer: connected source systems through connectors, collections and metadata the query layer can reason about, and a question that gives the system enough context to plan the query. If the underlying data model is incomplete or the business concept is still ambiguous, the chat will reflect that uncertainty.
What makes a strong chat question
The best chat prompts name the metric or entity you care about, the timeframe when time matters, and any filters or groupings needed to remove ambiguity. Questions like "Show weekly signups for the last 90 days by acquisition channel" are easier to answer well than broad prompts like "How are signups doing?" The more your wording matches the structure of the connected tools and your business model, the more grounded the result will be.
How chats fit into the platform
Chats are useful when you want to explore, follow up, and refine a question quickly. They work well for one-off analysis, early investigation, and the back-and-forth needed to arrive at the right framing. Once the answer becomes important enough to revisit regularly or share with the rest of the team, it usually belongs in a dashboard instead.