Kommon Poll AI can now retrieve relevant information from connected project databases and search indexes before responding, while also understanding the current filtering settings applied in Kommon Poll.

Previously, responses were based primarily on the conversation. With this update, Kommon Poll AI can understand who is asking, which project they are viewing, and which filters are currently active. This keeps its answers aligned with the exact data being analysed on screen.

What’s new

• Filter-aware responses: Kommon Poll AI uses the current dashboard filtering settings as a core part of the question context.

• Project-aware answers: It can retrieve relevant user, team, and project information.

• Improved data search: Elasticsearch integration helps it find relevant records across larger datasets.

• More accurate analysis: Responses can combine the conversation, active filters, project context, and underlying data.

• Improved system architecture: The retrieval workflow has been reorganised to support additional tools and data sources.

• Updated documentation: Technical guides now explain how Kommon Poll AI, databases, search tools, and filtering context work together.

When a user asks a question while viewing a filtered dataset, Kommon Poll AI can interpret the request using those active filters instead of analysing unrelated or unfiltered data.

This update makes Kommon Poll AI more context-aware, helping it understand not only the question being asked, but also the project and filtered view the user is currently working with.