Ursula
Captures personas and the why behind your product so development stays user-centric.
In one focused 10-to-20 minute session, move from concept to cost estimate and a blueprint your team and AI tools can execute.
Each agent runs a fixed stage so nothing material gets skipped. It is not an open-ended chat, but a guided workflow optimised for AI-readable requirements.
Captures personas and the why behind your product so development stays user-centric.
Defines what the software does, including security, scalability, and performance requirements.
Maps requirements to architecture, data schemas, APIs, and system constraints.
Produces a transparent story-point quote tied to the technical output.
Requirements ship as structured JSON or CSV for Cursor, Claude Code, Windsurf, and MCP-aware IDEs. One source of truth reduces context drift.
A transparent story-point model, not a black-box number. Complexity is tied to the technical spec so founders and buyers can act on a defensible fixed-price quote.
An authenticated API with OpenAPI 3.1 lets autonomous agents submit and retrieve requirements without the chat interface.
Each session is short enough to hold attention and long enough to extract real detail. It is structured for speed and precision, not open-ended chat.
Review, edit, and mark user stories and specs reviewed, plan your first release, and export to Jira, Markdown, or AI coding tools.
Scope and price an MVP before weeks of discovery calls, without writing code.
Bridge product and engineering with requirements AI coding tools can execute reliably.
Turn inbound leads into structured briefs and quotes in one session instead of a two-month cycle.
Feed Cursor and Claude Code structured context so builds stay maintainable as scope grows.
Fast prompt-based builds without detailed requirements tend toward spaghetti code. They become harder to maintain, with token costs that climb on every change. ChatStack structures requirements as data so AI execution stays dependable.
Sprint-only planning keeps product teams away from the tools that excel at multi-phase execution. ChatStack’s RADPAC approach (Requirements as Data, Plan and Context) gives AI a reviewed, task-based plan it helped create.
ChatStack is an AI PRD generator and software cost estimator. Its multi-agent interview produces structured JSON product requirements, user stories, technical specifications, and estimates for AI coding tools such as Cursor and Claude Code.
Founders scoping an MVP, product managers bridging engineering silos, agencies quoting faster, and teams using AI-assisted development.
Most sessions run 10 to 20 minutes. The interview is staged across four specialist agents so detail is captured without an open-ended chat.
ChatStack outputs a JSON PRD with user stories, requirements, technical specs, and a story-point estimate. You can export the results to Jira, Markdown, or AI coding workflows via MCP.
Yes. ChatStack maps the requirements and technical specification to story points, then produces a transparent software cost estimate for the proposed scope.
After your session, review and export outputs in ChatStack’s Product Management Portal. Read how we built ChatStack, or explore Enterprise AI Consulting if you want App Developer Studio to execute the brief as well as generate it.
Describe your idea or upload existing materials. ChatStack refines your requirements and generates a full project breakdown in minutes.