01
Structured context-to-PRD workflow
A product flow for gathering source context and turning it into a draft product requirements document that teams can inspect and refine.
Ragent case study
Designing an AI-assisted requirements engineering workflow
Simlyst engineered the product and AI workflow behind Ragent, helping turn discovery context into structured requirements artefacts while keeping review and delivery decisions with the product team.
- AI SaaS and product delivery
- Observable product capability
- No unsupported commercial metrics
In brief
What did Simlyst deliver for Ragent?
Product architecture, AI workflow design, LLM orchestration, requirements transformations and integration paths for downstream delivery tooling.
The engagement joined product design and technical implementation so the AI or analytical capability could sit inside a usable workflow, not remain a disconnected demonstration.
What you leave with
- Structured context-to-PRD workflow
- User-story generation
- Requirements interrogation
Starting point
The operational problem
Requirements work draws on conversations, source material, decisions and constraints that are often spread across several places.
Turning that context into a coherent product requirements document and implementation-ready backlog is repetitive, but it also requires judgement and traceability.
The product opportunity was to assist that synthesis without treating generated text as an approved requirement or removing the team’s responsibility to review it.
Delivery scope
Capabilities put into the product
These descriptions cover functional delivery. They do not infer adoption, financial performance or benefits that have not been measured and approved for publication.
02
User-story generation
Transformations that convert agreed product context into structured delivery artefacts rather than isolated free-form responses.
03
Requirements interrogation
An interrogation workflow designed to surface missing assumptions, contradictions and edge cases for human consideration.
04
Delivery integration path
Product and technical foundations for moving reviewed artefacts into Atlassian-oriented product delivery workflows.
Delivered outcome
What can be stated from the available evidence
The delivered product workflow brings source context, structured requirements drafting and review into one AI-assisted experience.
It demonstrates a bounded use of generative AI: the system prepares and interrogates artefacts, while people remain accountable for what is accepted and delivered.
Relevant capabilities
Explore the services behind this type of delivery
Start with the decision, not the technology
Need a working product, not an AI demonstration?
Describe the workflow, users, systems and evidence you need. We will help frame a delivery scope that tests the important assumptions without inventing an outcome in advance.