
Where Agentic AI Can Improve Business Performance
A framework for selecting AI workflows with a clear business owner, practical scope and measurable result.
RDMI research
Explore where AI can help, how to build it and what to check before putting it to work.

Selected reading

A framework for selecting AI workflows with a clear business owner, practical scope and measurable result.

How AI connects customer, pipeline, service, billing, and product signals into revenue decisions and automated next actions.

Practical controls for agentic workflows: access, approvals, audit trails, evaluations, escalation, privacy, and production monitoring.
Explore the library
Explore the decisions, systems and controls behind useful AI workflows.
6 articles

A framework for selecting AI workflows with a clear business owner, practical scope and measurable result.

How AI connects customer, pipeline, service, billing, and product signals into revenue decisions and automated next actions.

Practical controls for agentic workflows: access, approvals, audit trails, evaluations, escalation, privacy, and production monitoring.

Why production AI needs reusable workflows, evaluation, context design, and operating rules rather than isolated prompt craft.

A practical framework for turning AI experiments into production workflows, team adoption, governance, and measurable business value.

How RAG, knowledge graphs, document intelligence, structured data, and evaluations create a trusted foundation for workflow AI.
From insight to action
Identify the workflow worth improving, establish the business case and define what successful delivery requires.