Artificial intelligence is no longer just a buzzword in software development. It's actively reshaping how we approach quality assurance. At NUCIDA Group, we decided to put this promise to the test. I dove deep into TestStory.ai, an AI-powered platform designed to generate comprehensive test cases from simple natural language prompts. The big question on my mind: Can this tool genuinely save QA engineers hours of manual work while delivering high-quality, executable test cases? Spoiler: The results were surprisingly impressive, especially for functional testing, but with some clear boundaries and one feature that showed both wow-factor and room for improvement
TestStory.ai is a web-based platform that turns simple English prompts into complete, well-structured test cases. It has a Diagram feature(which is a premium feature). It comes in various subscription plans, from Daily to enterprise level. If you want a free ride, it provides you with a limited free version as well. Moreover, you can also export the results in various formats like PDF, MD file, CSV, etc.
It is quite user-friendly. You just have to provide a prompt, and Boom! It generates within seconds. You can also import test cases from other platforms like Jira. Within seconds, it produced clear, step-by-step test cases with expected results. It even categorized them as functional, boundary, or negative, just like we do manually. Here is a look at its interface:
It supports exporting to popular formats (PDF, Markdown, CSV), imports from tools like Jira, and offers subscription tiers from daily access to enterprise plans, with a limited free version to get started. No steep learning curve here; just prompt and go.
To understand how powerful TestStory.ai really is, I decided to test it using three different levels of prompts: Easy, Intermediate, and Hard. Each level represented a different kind of QA scenario, from a simple mobile form to a multi-role web platform. This helped me evaluate how well the AI adapts to complexity, logic, and coverage.
I created a prompt: “Generate test cases for a mobile app’s contact form with fields for name, email, phone number, and message. Include validations for required fields, invalid email formats, and character limits.”
Boom: six polished test cases in seconds. It covered happy paths (successful submissions), error handling (missing required fields and invalid emails), and boundaries (maximum message length). The data examples felt realistic (“John Doe”, “john.doe@example.com”), and expected outcomes included precise error messages and UI feedback, such as field highlighting.
For simple UI forms, this was near-perfect, ready to copy-paste into TestRail, Xray, or any test management tool with zero edits.
Next up, something more interactive. The next prompt is more complex:
“Create detailed test cases for a note-taking web application that supports creating, editing, deleting, and searching notes. Include both UI and functional scenarios such as autosave, search accuracy, and undo actions.”
The AI delivered over ten robust cases. It handled full CRUD flows, UI behaviors (button states, cursor changes), autosave timers, browser-close recovery, and smart search logic (partial matches, case sensitivity, empty results).
What impressed me most was how it logically connected test flows:
After creating a note, the next test involved editing and verifying updates.
The autosave test included a timer and browser close scenario, something only experienced testers usually consider.
Search tests included partial matches, case sensitivity, and no-result handling.
This round showed genuine reasoning, not just keyword repetition. The AI was thinking through the workflow and creating a realistic QA narrative.
Hard Prompt: The Learning Management System (LMS)
Finally, I gave it a complex, enterprise-level challenge: “Generate comprehensive test cases for an online learning management system (LMS) that supports user roles (Admin, Instructor, Student), course creation, video streaming, quizzes, and progress tracking. Include security, performance, and role-based access scenarios.”
TestStory.ai generated over twenty structured test cases covering:
Role-based authentication for each user type.
Course creation and content upload workflows.
Video streaming and quiz attempts.
Progress tracking dashboards for both students and admins.
Security and access control, ensuring students can’t access admin pages.
Even performance and concurrency testing, like multiple users streaming at once.
Each case included specific inputs, expected outcomes, and realistic error messages. It didn’t just stop at simple validation; it tested invalid credentials, missing titles in course creation, and invalid file types during upload. Here is one of the test cases that I got as a result:
Premium Feature Spotlight: The Diagram (AI Metadata) Tool
We recently gained early access to TestStory.ai's premium Diagram feature. Drag any image onto the canvas, and the AI analyzes it to extract metadata: type (UML sequence, flowchart, BPMN), audience (business/technical), tags, confidence-based title, and a short description.
I stress-tested it with everything from polished UML sequence diagrams to a blurry photo of my coffee mug. The good, the bad, and the bogus all went in! Below is a quick tour of what the feature does right, where it stumbles, and the single fix that would turn it from “cool demo” into “production-ready”.
But here's where it stumbled: non-diagram images (Instagram sunsets, blank paper, cartoons) were still processed and returned confident (but nonsense) metadata.
The simple fix? Implement a confidence gate or primitive detection (arrows, boxes, lifelines) to reject irrelevant uploads with a friendly message: “This doesn't look like a process diagram. Please upload a valid UML, BPMN, or flowchart.”
One of the standout premium capabilities of TestStory.ai is its Process Diagram analysis (often referred to in early access as the "Diagram (AI Metadata)" feature), which allows users to upload visual process flows and automatically generate comprehensive, structured test cases directly from them. This tool leverages advanced AI vision models to interpret a wide variety of diagram types, supporting over 19 formats including BPMN, flowcharts, swimlanes, UML (sequence, activity, class, use case, state machines), ERD, data flow diagrams, system architecture diagrams, Gantt charts, org charts, mind maps, journey maps, Kanban boards, SIPOC, and more. Compatible file formats include Visio (.vsdx), Lucidchart exports, PDF, PNG, and JPEG, making it easy to drop in diagrams from popular tools like Lucidchart, Visio, Draw.io, or even screenshots/hand-drawn sketches (though best results come from clean, structured diagrams).
Here's how it works in practice: Navigate to the dedicated Process Diagrams section in the web app, upload your file (with an optional title and description for context), and the AI quickly analyzes the visual elements, mapping out steps, decision points, branches, roles, sequences, and flows. It then produces detailed test cases that cover happy paths, alternative flows, edge conditions, error handling, role-based access, and validations derived logically from the diagram's structure. You can review, edit, and export the generated tests just like any other output from the platform. In early testing, it excelled at recognizing technical and business diagrams (e.g., perfectly tagging a taxi-booking sequence or photosynthesis process flow with relevant keywords), but non-diagram images (like photos or unrelated graphics) could sometimes trigger misleading metadata, highlighting the value of its specialized focus on process visuals.
This feature bridges a common gap in QA: many requirements arrive as visual artifacts rather than text, and manually translating complex diagrams into testable scenarios is time-intensive and error-prone. By automating this, TestStory.ai empowers teams to achieve faster, more accurate coverage for workflow-heavy systems, whether enterprise software, microservices interactions, or even non-software business processes, turning static visuals into dynamic, verifiable test documentation in seconds. It's particularly powerful when combined with the platform's other inputs (user stories, code, issues) for hybrid, multi-source test generation.
In the rapidly evolving world of software quality assurance, AI is transforming how teams create, execute, and maintain tests. Two notable players, TestStory.ai and Testim (now part of Tricentis), offer AI-driven solutions but target very different parts of the testing lifecycle.
TestStory.ai excels at rapid test case generation from natural language, while Testim focuses on AI-stabilized automated test execution for UI and functional testing. If you're deciding between them (or wondering how they complement each other), here's a clear, practical comparison based on their core capabilities, strengths, limitations, and ideal use cases.
TestStory.ai: An AI-powered QA agent specialized in generating high-quality, structured test cases (manual or preparation for automation) from user stories, issues, epics, process diagrams, requirements, source code, or free-form prompts. It's a web-based platform (with API and integrations like Jira, Linear, GitHub) designed to accelerate the early stages of QA, turning requirements into verifiable, best-practice test documentation in seconds to minutes.
Testim: A full AI-powered test automation platform (Tricentis Testim) for authoring, executing, and maintaining stable end-to-end automated tests, primarily for web, mobile, and Salesforce applications. It uses record-and-playback combined with heavy AI (smart locators, self-healing, agentic automation) to create resilient tests that require minimal maintenance even as the UI changes.
| Aspect | TestStory.ai (TestQuality) | Testim (Tricentis) | Winner / Notes |
|---|---|---|---|
| Primary Focus | Test case generation & documentation | Automated test creation, execution & maintenance | Depends on need |
| AI Usage | Generates complete test cases from prompts, stories, diagrams, and code | AI for smart locators, self-healing, agentic NL test creation, stability | Testim has deeper runtime AI |
| Input Types | User stories, Jira issues, diagrams (premium), requirements, code/repos, free text | Natural language prompts (agentic), recorded user flows, code steps | TestStory.ai has more versatile inputs |
| Output | Structured manual/functional test cases (steps, expected results, categories: positive/negative/boundary) | Executable automated tests (low-code/record + code flexibility) | TestStory → docs; Testim → runnable scripts |
| Execution | No built-in execution (focus on generation; export to PDF/MD/CSV or integrate) | Full execution in cloud/local, cross-browser, parallel runs, reporting | Testim |
| Stability & Maintenance | N/A (test cases are static docs) | Excellent—AI self-healing reduces flakiness by learning app changes | Testim |
| Supported Apps | Any (web, mobile, enterprise, non-software workflows) via description | Web, mobile, Salesforce (strong in UI/functional E2E) | Testim more specialized |
| Integrations | Jira, Linear, GitHub, ClickUp, API, MCP tools (Claude, Cursor, VS Code) | CI/CD pipelines, dev tools, Salesforce ecosystem | Similar breadth |
| Ease of Use | Extremely simple: prompt → generate in seconds | Record-and-playback + AI suggestions; low-code with code extensibility | TestStory.ai is faster for beginners |
| Pricing | Free tier (limited), subscription plans (daily to enterprise), credits-based in some integrations | Free account/trial, paid starts ~$450/month (usage-based), enterprise custom | TestStory.ai is likely more accessible for small teams |
| Best For | QA teams are drowning in manual test writing, needing fast coverage from requirements | Teams running automated regression/UI suites who hate flaky tests | — |
Building top-notch software doesn’t have to be a struggle. At NUCIDA, we’ve cracked the code with our B/R/AI/N Testwork testing solution - pairing our QA expertise with your test management tool to deliver streamlined processes, slick automation, and results you can count on. On time. Hassle-free. Ready to ditch future headaches? Let NUCIDA show you how!
Why Choose NUCIDA?
For us, digitization does not just mean modernizing what already exists but, most importantly, reshaping the future. That is why we have made it our goal to provide our customers with sustainable support in digitizing the entire value chain. Our work has only one goal: your success!
Don’t let testing slow you down. Explore how consulting services can make your software quality soar - headache-free! Got questions? We’ve got answers. Let’s build something amazing together!
Across all three prompts, TestStory.ai consistently produced structured and readable test documentation. It maintained a good logical flow from action to expected result and showed consistency across mobile, web, and enterprise use cases. However, as complexity increased, its limits became visible. It still doesn’t handle API testing, backend validations, or creative exploratory cases. Still, for functional QA coverage, it’s one of the most efficient AI tools I’ve tried. This experiment reminded me that the future of QA isn’t about choosing between humans and AI, it’s about how we can work better together. TestStory.ai is a great example of AI making testing more accessible, less tedious, and more intelligent.
Compared with Testim, both represent the future of QA: less tedium, more intelligence. The right one depends on whether you're stuck in the test creation bottleneck or the test maintenance/flakiness bottleneck. Have you used an AI-powered QA tool? Which part of the testing process pains your team most? Drop a comment. I'd love to hear your views!
NUCIDA QA experts can support you in implementing flawless AI-powered testing solutions to improve your QA services. We transform software testing with tailored strategies, optimized processes, and strong governance. We’ve helped leaders cut testing effort and deliver flawless products on time. With certified professionals, cutting-edge methodologies, and a passion for excellence, we’re not just a vendor; we’re your partner in success. Ready to boost your business? Choose NUCIDA today!
Want to know more about the new Xray AI features? Watch our YouTube video, Revolutionize QA with Xray's AI, to see how AI works in Xray.
Pictures / Logos from pixabay.com, TestQuality, and NUCIDA Group
Article written by Eman Rani and published by Torsten Zimmermann