Client context
A company with a clear business problem but no technical specification and no internal AI team. Details are anonymized at the client's request.
Case study
From a business conversation to an implementation backlog
An anonymized example of using the Business Requirements Generator to start an automation project without a technical specification — turning a conversation into structured requirements, task cards and a backlog.
The business problem
They knew which process was painful but couldn't translate it into requirements a team could build from.
The process before Mindstructs
Earlier attempts stalled at the documentation stage — meetings produced notes, not a plan, and the project never started.
Discovery and requirements
Using AI-guided discovery, an AI Business Analyst interviewed stakeholders about goals, users, data and constraints, and structured the conversation into clear requirements.
The solution we designed
Requirements became task cards with structured fields, sequenced into a prioritized backlog with estimates and dependencies — an executable plan, not a slide deck.
Implementation
The backlog flowed straight into delivery; work was scoped, assigned and built from the same task cards produced in discovery.
Technologies used
The Mindstructs platform's AI discovery and task-card generation, feeding the implementation backlog.
Results
The project moved from stuck-on-documentation to a concrete plan and first delivery, with the client owning the requirements and backlog throughout. Outcomes are described qualitatively.
What was supported after launch
We continued to refine the backlog and supported the implemented work as the process evolved.
Related services
Could this work for your process?
Describe your process and where it slows down. We turn it into structured requirements, an AI workflow and a working, supported solution.