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Turn Figma designs into test-ready stories with AI

Translate Figma designs into automated test scripts and user stories to align design, development, and quality assurance (QA) teams.

7th August, 2026
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Why do great designs still ship as delayed, defect-prone releases? Because turning them into requirements stays manual, and that’s where delivery breaks. Orchestrating Figma into executable Gherkin stories and test scripts closes the gap.

AI design translation: The path between vision and execution

  • AI-driven parsing translates visual UI designs directly into structured user stories, significantly reducing manual interpretation errors and bias.
  • Teams can align design intent with acceptance criteria much earlier in the process, speeding up delivery.
  • Automated test generation delivers Cyara-ready scripts instantly.
  • This empowers QA engineers to validate requirements earlier and mitigate downstream defects.
Author Details
Hema Nandagopal

Architect – Digital Engineering, Brillio

Closing the design-to-delivery gap

The persistent gap between design intent and implementation reality challenges even the most agile delivery environments. UX designs often look perfect on Figma, but translating those visual assets into clear requirements and test cases involves manual effort, interpretation, and rework. Downstream activities like writing user stories, defining acceptance criteria, and creating test are still manual in many environments. This creates inconsistent interpretations, missed edge cases, and costly delays in development and testing. The Figma to Gherkin and Cyara Orchestration Platform addresses this with an AI-powered approach that directly converts design artifacts into structured requirements and test scripts. This brings design, development, and quality assurance into true alignment.

Figma to Gherkin and Cyara Orchestration Platform

The platform is an AI-driven service that integrates securely with Figma to intelligently parse design hierarchies. By leveraging advanced LLMs, the system understands UI patterns, user flows, and interactions. It processes this visual and structural data to generate:

  • Gherkin-based user stories
  • Detailed acceptance criteria
  • Cyara-compatible automated test scripts

What the solution is designed to solve

Designed with clear business outcomes in mind, the platform automates requirement generation to ensure exact alignment between design inputs and acceptance criteria. This reduces manual effort and enables early test automation in the software development lifecycle. Current capabilities include Figma design ingestion via REST APIs, hierarchical parsing of boards, pages, and sections, and user-controlled drill-down for selective AI generation. Direct frontend or backend code generation, real-time design editing, and integration with non-Figma design tools remain out of scope to maintain a strict focus on requirement accuracy.

Intelligent infrastructure: How we drive seamless design-to-test transformation

How the architecture works

The platform relies on a secure Figma integration layer that authenticates via API tokens and fetches design data. A processing engine maps hierarchical elements and extracts metadata like labels, components, and interactions. Next, an AI interpretation layer leverages tools like Claude to understand UI patterns and generate Gherkin syntax. An output generator then produces the feature files and automation scripts through an intuitive user interface that offers file selection, preview, and export capabilities.

An end-to-end workflow

The user journey prioritizes speed and intuition. Users authenticate and provide their Figma API token, prompting the system to fetch the file structure. Once a user selects the required board, page, or section, the platform parses the components and applies AI to process the design context. The system generates the necessary Gherkin stories and Cyara test cases, which the user can then review and export. This streamlined workflow accelerates early validation and faster delivery.

Security, performance, and risk resilience that make a difference

Enterprise-grade deployment requires strict adherence to non-functional expectations. The platform efficiently handles large Figma files and scales to support multiple users and projects. Security is managed via encrypted token handling with no persistent storage, ensuring reliable and repeatable output generation. To mitigate risks like design misinterpretation, the system uses improved prompt engineering and validation. File processing delays are handled through caching and incremental parsing, while API rate limits use throttling and retry mechanisms.

Charting a path of future innovation and measurable impact

The platform is currently hosted in a controlled beta environment accessed via a secure endpoint on an approval basis. Future enhancements will support additional design tools like Adobe XD and Sketch, integrate directly with Jira and Azure DevOps, and enable code generation from Gherkin for behavior-driven development pipelines. Strategic success will be measured by tracking the reduction in requirement creation time, the accuracy of generated stories, cross-team adoption rates, and improved test coverage through Cyara automation.

Reimagining design-led delivery: Closing the last mile gap

This orchestration platform bridges a long-standing gap between design and delivery. By combining API-driven design ingestion, AI-powered interpretation, and automated test generation, it enables organizations to deliver faster with higher accuracy and confidence. It represents a fundamental shift toward true design-driven development.

Orchestrating cross-functional impact: How different roles benefit

Product Managers

Validate requirements against design intent early, before development starts, catching gaps when they are cheapest to fix.

Designers

UX/UI designers see their intent preserved end-to-end, so what ships matches what was designed, without translation loss.

Developers

Receive clear, unambiguous Gherkin stories with built-in acceptance criteria, removing guesswork and back-and-forth over what to build.

QA engineers

Get ready-to-run Cyara scripts the moment designs are set, enabling earlier testing and fewer defects downstream.

DevOps

Integrate generated outputs directly into continuous integration and continuous delivery (CI/CD) pipelines for faster, more reliable releases.

Strategic imperatives: Unlocking value from automated design orchestration

  • Direct conversion of Figma designs into executable Gherkin requirements eliminates manual translation bottlenecks and associated interpretation biases.
  • Enterprise teams realize faster time-to-market and lower defect rates through early, AI-powered test automation generation.
  • Strategic investment in design orchestration fosters true alignment across product, development, and quality assurance disciplines.

What teams must ask before rolling this out

No. It authenticates through encrypted API tokens and does not persist your design data. Files are parsed in-session and used only to generate stories and scripts, keeping your design IP in your control.

The AI produces a structured first draft, not a final artifact. Product managers and QA engineers still review and approve every story before it enters the pipeline. The goal is to remove manual effort, not judgment.

No. It removes the repetitive work of hand-writing stories and test cases so those roles focus on edge cases, acceptance criteria, and validation. They shift from authoring to refining.

The current release is optimized for Figma inputs and Cyara outputs. Support for Adobe XD, Sketch, Jira, and Azure DevOps is on the roadmap, so other stacks can plan a phased adoption.

Because the output is Gherkin, it drops into behavior-driven development pipelines with minimal change. Stories are generated early, letting you shift testing left and validate requirements before development begins.

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