How Screeb AI works (business overview)

Screeb AI is a product-assistant workflow that helps teams understand user behavior and make faster product decisions from their Screeb data.

What Screeb AI is designed for

Screeb AI is built to answer product questions such as:

• What changed in user engagement?
• Which segments are most impacted?
• What should we investigate next?

Instead of manually building every query, teams ask a business question in plain language and Screeb AI orchestrates the analysis.

End-to-end workflow

1. Question intake
   A user sends a product question from the Screeb interface.

2. Context alignment
   Screeb AI applies workspace, organization, and user context so results stay scoped to the right data perimeter.

3. Task orchestration
   A supervisor agent breaks the question into smaller analytical tasks and routes them to specialized tools/sub-agents.

4. Data retrieval and checks
   The system calls the required tools, gathers relevant metrics/events, and keeps track of reasoning steps.

5. Synthesis
   Screeb AI combines tool outputs into a clear, business-oriented response with the key findings and rationale.

6. Actionable output
   The final answer is returned to the user to support product decisions (for example prioritization, investigation, or follow-up experiments).

Business value

• Faster analysis: less manual exploration before finding useful signals.
• Better alignment: teams share a common, explainable reasoning path.
• Safer decisions: scoped context reduces cross-workspace confusion.
• Operational visibility: logging and reasoning traces improve auditability and support.

What Screeb AI does not replace

Screeb AI supports product decision-making, but it does not replace:

• product strategy ownership,
• experiment design,
• stakeholder validation.

It is a decision-support layer that accelerates understanding and execution.