Start smart: A new era in QA test coverage planning
Before you can test software, you need to know what to test. That’s where many QA teams stall out. They don’t have the right software testing tools for mapping the app, identifying user paths, and determining testing priorities. So, building a test plan can take days (or more) of manual work. It’s often slow, frustrating, and error-prone.
Even then, you’re often left wondering if you missed something important.
It’s not a recipe for confidence.
The “blank page problem” can mean skipping QA tests altogether and just hoping for the best. Or the lack of a comprehensive app map (and the resulting test plan) can lead to guesswork, causing quality issues and a poor user experience.
For those who already have some tests in place and aren’t contending with a blank page, the path to coverage improvement can still be hazy.
AI testing tools can change the game here.
With AI Test Planner, Rainforest QA now does the heavy lifting of mapping potential coverage for you — whether you’re starting from scratch or not.
Don’t just take our word for it, though. Here’s what one beta tester had to say:
“It gave us a solid foundation and confidence that our key use cases are covered.”
– QA Engineer at a Medtech Compliance App
(Rainforest customer & beta tester)
How AI Test Planner works
AI Test Planner uses our proprietary AI crawler to map your app from a starting URL, methodically exploring the entire product. Over a few hours, Rainforest’s AI crawler moves through the major features and common user paths. It then compiles an AI Test Plan, which is a structured view of your app (as a PDF), that can become your foundation for planning test coverage.
You’ll see your app clearly mapped out — organized by modules, features, and flows — giving you a practical view of what might need testing.
From there, your team can apply their in-depth knowledge of the app to prioritize and quickly finalize a test plan. (And Rainforest can then help rapidly create test cases.)
As with all aspects of Rainforest’s AI testing tools, our goal is to use QA automation and AI to reduce manual effort and risk while keeping humans in the loop for contextualization.
This saves time while ensuring you can trust your QA processes and outcomes.
What you’ll get with AI Test Planner
Not all software testing tools are created equally. Here’s what you’ll get with Rainforest’s AI Test Planner:
- Comprehensive map of your app — all major areas and paths captured automatically by our AI crawler
- Actionable output — downloadable PDF structured by modules, features, and user journeys
- Deeper exploration — multi-hour AI crawl that systematically uncovers more than surface-level pages
- Confidence from day one — gain visibility and move faster toward meaningful test coverage
- Plain English — no need for technical expertise to interpret and implement the results (all part of Rainforest’s no-code ethos)
Here’s what our AI testing tool looks like inside Rainforest:
Why it’s different
Most other AI testing tools for QA focus on generating individual tests or replaying user traffic, which can leave major coverage gaps. Plus, they don’t provide sufficient visibility into your actual coverage.
In other words, you won’t know what you don’t know.
Rainforest’s AI Test Planner goes broader and deeper — building a holistic coverage plan that helps teams see the full picture before writing a single test.
This is the first AI feature designed not just to execute on QA, but to strategize coverage plans.
Here’s what a sample AI Test Plan looks like:
Who it’s for
- QA leaders who want a clear, defensible starting point for test planning without heavy manual effort and are ready to invest in AI testing tools
- Developers who need test coverage they can trust without adding to their workloads
- Engineering leaders who want quality outcomes they can stand behind
Advancing AI-Powered QA testing strategy
AI Test Planner is a major step forward in Rainforest QA’s mission to help teams simplify QA at every stage of the process, from mapping potential coverage to creating test cases to healing failing tests and adding coverage as new features are shipped.
AI Test Planner helps teams answer the thorny question of, “What do we even test?” so they can get to planning and executing tests faster.
Get started today
AI Test Planner is now available to all Rainforest QA customers.
See how Rainforest’s AI testing tools can help you start smarter.
New to Rainforest? We’d love to show you around:
Already a Rainforest user? Check it out in the platform today:
For more information on how AI Test Planner works, see our Help Docs.
To read more about why customers rate Rainforest QA 4.9 / 5 stars, visit Capterra.
FAQs about AI Test Planner
Can I start using AI Test Planner today?
Yes, our AI test planning feature is available to all Rainforest customers in the platform starting today.
How do I use AI Test Planner results to plan tests?
You can review the AI Test Plan and determine, based on your in-depth knowledge of the product, what should be included in your test plan. So it provides a starting point to avoid the “blank page” issue.
I have multiple applications. Can I still generate an AI test plan?
Yes, you’ll just need to run the crawler on each application separately.
Can I run the crawler again in a few months to ensure my team is up-to-date on coverage?
Yes, there are no limits to how often you can generate a new plan. AI Test Planner is designed both for teams just getting started with QA testing and those who have tests in place but need to map and extend coverage.
Is the test plan going to include all possible paths?
No, the crawler won’t be able to uncover every single path. It will go about four levels deep into each page of your application. The Planner will then build a test plan with as many of the covered paths as possible. It should give you a high-level overview that you can use as a starting point.
Can I limit the crawler to just part of my application?
At the moment, no. The crawler will navigate through as much of the application as possible. It will only limit itself when encountering a new subdomain. When this happens, it will attempt to assess whether it’s still in the same application or not (e.g., it shouldn’t explore your blog or help center, even if that’s linked from your application).
