Consulting service
AI Workflow and Transformation Sprint
Choose the right workflow, design a practical AI solution, define human controls, and leave with a plan the team can build and use.
What will my team have at the end of the AI workflow sprint?
Your team will have one clearly defined AI use case, a practical solution design, a tested first version or build plan, human review steps, and clear ownership for launch and improvement.
What this engagement helps solve
Choose the right workflow
Identify the repeatable task, decisions, information, handoffs, and review points worth improving.
Design the solution
Choose the right mix of AI models, trusted sources, tools, data, and human control without adding unnecessary complexity.
Make it usable
Define quality checks, ownership, instructions, and what should happen when the AI is uncertain or wrong.
How the work happens
- Understand the current work
Map how the task works today, where time is lost, what information is needed, and which decisions require a person.
- Build and test the smallest useful version
Test the complete workflow, including source quality, tool use, output quality, and common failure cases.
- Prepare the team to launch
Document the controls, owners, measures, instructions, and the next improvements to consider.
What is not included
Fully autonomous publishing, removing required human review, open-ended custom software, or promises that an AI model will never make a mistake. Additional work can be discussed and priced separately.
Related proof
Governed multi-agent publishing workflowRelated thinking
How to choose an AI workflow to automate