Use shared company knowledge to create documents and repeatable team workflows
Aurora AI is a shared workspace for teams that want AI responses to reflect their own company knowledge. It combines project organization, reusable knowledge, collaborative writing and guided workflows. The emphasis is on giving a team common context, rather than leaving each person to recreate the same background information in separate conversations.
Workspaces can organize activity around a department, project or client. Knowledge Docs hold information that the AI can reference, while Aurora Docs provide a place to take notes and develop drafts collaboratively. The official feature page describes turning a working note into knowledge with a single action. This makes a distinction between material still being developed and material a team wants to reuse as context.
The AI chat is designed to use stored knowledge when answering questions. Responses can be copied, bookmarked and traced back to source material. Smart Flows add a guided sequence of instructions for recurring tasks, allowing a team to reuse a process instead of starting from a blank prompt every time. Examples on the product site cover sales scripts, positioning, case studies, webinar planning and other business writing tasks.
Liquid Docs is described as a way to turn longer strategies, reports or ideas into presentation-ready formats. Together with the document workspace, this supports moving from notes to a more structured deliverable without repeatedly changing tools. It is still important to review the resulting argument, figures and citations rather than treating a polished layout as proof that the underlying claims are correct.
Aurora offers a thirty-day trial followed by per-seat Pro pricing, with different monthly and yearly rates. A useful evaluation would begin with a limited collection of approved company documents and one repeatable task. Team members can then check whether the generated output uses the right context, whether permissions are appropriate and whether the workflow genuinely saves duplicated effort. Public pages do not specify a complete external integration catalog or model roster, so those requirements should be confirmed before a wider rollout.
