Your regression suite passes. Every documented test case runs successfully. The release looks ready.
Then a customer takes a perfectly valid path through your application—and something breaks.
Nobody skipped a test. Nobody ignored a requirement. The problem was a workflow your team never thought to include.
That is one of software testing’s hardest challenges: how do you test for scenarios you haven’t identified?
AI test discovery helps teams address that question by looking beyond the regression tests they already wrote.
Your Regression Suite Reflects What You Know
Existing test cases represent valuable knowledge. They capture business requirements, critical workflows, historical defects, and the experience of people who understand your application.
But they also reflect decisions about what to test.
Teams naturally prioritize familiar journeys: create an account, submit an order, update a profile, complete a transaction. Those tests establish an essential baseline.
Users, however, don’t always follow the sequence your test author imagined. They change their minds, revisit earlier steps, encounter validation errors, and resume unfinished tasks.
A regression suite can validate its intended scope while leaving meaningful combinations unexplored.
The Missing Tests May Be Ordinary User Behavior
Consider an online ordering application.
Your existing tests might confirm that a customer can add a product, apply a discount, and complete checkout.
But what happens when that customer applies a discount, changes the order quantity, removes an item, and then updates the delivery address?
Each action may work independently. The sequence may expose a problem with pricing, eligibility, or the information carried between steps.
This illustrative example isn’t an obscure misuse of the application. It is a valid customer journey.
The missing test exists in the relationship between application states.
Meet AISG Bug Hunter
Appvance AISG Bug Hunter addresses this discovery challenge.
It uses the AIQ Digital Twin to understand application states, elements, transitions, and business behavior. It then explores those states against business requirements to identify additional valid test flows beyond the existing regression pack.
That connection to requirements matters. More activity alone doesn’t establish better testing. Additional flows need to exercise meaningful behavior with expected outcomes grounded in what the application should do.
AISG Bug Hunter helps teams broaden their view of where testing is needed.
Automate What You Know. Discover What You’re Missing.
Within Appvance AIQ, GENI and AISG Bug Hunter address complementary problems.
GENI converts existing natural-language test cases into production-grade Playwright Python. It helps teams turn established regression knowledge into automation.
AISG Bug Hunter helps uncover important flows those test cases don’t already describe.
Together, they support a broader quality strategy: preserve the value of existing tests while expanding visibility into relevant application behavior.
Ask a Better Release Question
“How many tests passed?” remains useful. But it should lead to another question:
“What meaningful behavior haven’t we tested yet?”
Appvance’s concept of Application Coverage brings attention to the application states that matter to the business, beyond the boundaries of a predefined checklist.
Your regression suite protects what your team already knows.
AI test discovery helps reveal what deserves attention next.
Explore Appvance AISG Bug Hunter—and find the important tests you didn’t know you needed.
