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Departments, risk analysis and insights

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Conversa Labs

Conversa Labs

Last updated on Jun 27, 2026

Overview

The Account Brain organizes Maestro's work into departments — operational areas such as support, sales, risk, finance and knowledge. Each department runs periodic routines over the account's conversations and data and produces two main outputs: risk analysis (signals of problems or attention) and insights (opportunities and recommendations).

Each department has an autonomy level. At conservative levels, it only observes and suggests (read-only). At levels with human approval, it proposes actions that wait for your confirmation before any execution. Nothing destructive or final happens automatically without that approval.

Prerequisites

  • An account with Maestro and the Account Brain enabled.
  • Administrator permission to create/adjust departments and autonomy.
  • Recommended: complete the onboarding (which already provisions the basic departments) and feed the knowledge corpus for richer analysis.

Step by step

  1. Open the Account Brain and go to the Departments area.
  2. Review the provisioned departments (or create/enable the ones that make sense).
  3. Set the autonomy level of each one (for example, read-only or with approval).
  4. Let the routines run: Maestro processes conversations periodically.
  5. Follow the risk analysis and the insights feed generated by the departments.
  6. When there are proposals that require approval, review and confirm (or decline) each one.

Settings & options

  • Departments: areas such as support, sales, risk, finance and knowledge.
  • Autonomy per department: from the most conservative (observes and suggests) to the most autonomous (executes what was approved). Start conservative and evolve.
  • Human approval (HITL): proposals wait for your decision before being executed.
  • Insights and risk: panels that consolidate what Maestro found, with source references when applicable.

Use cases

  • Identify at-risk conversations (dissatisfaction, delays, churn) before they become problems.
  • Discover sales opportunities and next-action recommendations.
  • Distribute intelligence across areas, with the right level of automation for each one.
  • Standardize the operation with routines that run on their own and report what matters.

Tips, limits & best practices

  • Start with conservative autonomy (read-only or with approval) and increase as trust grows.
  • The richer the knowledge corpus, the more accurate the risks and insights.
  • Departments may appear empty at first — they populate after the routines run.
  • Periodically review pending proposals so the queue doesn't pile up.

Troubleshooting

  • Empty departments: confirm they are enabled and wait for the routines; check whether onboarding/ provisioning was applied.
  • No insights/risk: enrich the knowledge and confirm there are enough conversations to analyze.
  • Proposals don't execute: at approval levels, they depend on your confirmation — review the pending items.

See also