Digital.ai Testing — Premium Tier
Know how it's running. Know why it broke.
One place to see your testing program. One clear answer when something breaks.
Premium includes Advanced Analytics · AI-Powered Root Cause Analysis
The gap
Testing leaders ask the same questions all the time.
- Which devices are earning their keep?
- Is the platform being used across teams?
- Why did this test fail?
The information to answer them exists — it's just spread across different places, and someone has to pull it together first. That takes time, and time is where the risk builds.
A failure that takes too long to explain gets rerun, then deferred, then written off as flaky. Sometimes it's a real defect, and it reaches production.
Premium brings it together in the product. Advanced Analytics connects the signals across the program. AI-Powered Root Cause Analysis connects the evidence behind any single failure.
Advanced Analytics
Advanced Analytics tells you where to look.
Your testing program already generates the data. Advanced Analytics connects it inside the platform — no export, no separate BI tool to stand up.
Can you answer these questions today?
I oversee both our infrastructure and testing program. I'm constantly being asked how our resources are being used. Which devices are in demand? What's sitting idle? Advanced Analytics gives me a much easier way to answer those questions.
— Large Financial Services Customer
Capacity you already own
A quiet window is room to redistribute automated runs before you add anything new. A device carrying real allocation but little return is one you can point somewhere else.
Read more: The Spreadsheet Is the Tell →AI-Powered Root Cause Analysis
Root Cause Analysis tells you what to do about it.
Your automation tells you when a test failed. It doesn't tell you why. Root Cause Analysis reasons over the artifacts already attached to that run — device logs, cloud and server logs, screen captures — and returns the most probable cause with the evidence behind it.
You start where you already are — the failed test inside the existing report. No new tool, no new workflow, nothing to export.
The analysis runs against every artifact behind that run — including the server-side and Appium logs that usually hold the answer and rarely make it into a manual export.
Most probable cause, a confidence score, and the specific log line or test step behind it — so you can verify it yourself, route it to the right owner, and decide to fix, rerun, or defer with evidence attached.
Confidence you can check
The score reflects how much the evidence agrees — not how certain the model sounds. It is never inflated to look more certain than the underlying data allows.
Confidence rises when
- Multiple independent sources point to the same failure point
- The evidence is an explicit error, not an inference
- The sequence from trigger to failure traces cleanly
Confidence falls when
- A log source was unavailable
- Only one source supports the conclusion
- A competing explanation could not be ruled out
Isn't this the same as pasting logs into a chatbot?
No. A general-purpose model only sees what someone manually exported, and can't point to the artifacts it used. This analyzes the artifacts behind that specific run — including platform-level logs the report doesn't surface — and cites the evidence for every conclusion.
You need high confidence in the results
Watch how one click turns a failed test into a probable cause, a confidence score, and the exact evidence behind it — no digging through logs required.
Read more: The Trust Problem in AI Test Failure →Why this is one tier
Four decisions. One tier.
A testing leader makes the same handful of decisions every quarter. Today most of them are made on instinct, or on a number somebody assembled by hand.
Should we buy more devices — and which ones?
Utilization by device and OS version, with peak demand windows, against what you already own.
Advanced AnalyticsIs this platform earning its place across teams?
Adoption by team and project, and how it's trending, without a recurring export.
Advanced AnalyticsIs our testing effort going where the risk actually is?
Execution volume and trend across projects, applications, and devices.
Advanced AnalyticsIs this release safe to ship?
A probable cause and traceable evidence for the failures standing between you and the go/no-go.
AI-Powered Root Cause AnalysisKnow how it's running. Know why it broke.
See both capabilities against your own testing program, with your own devices and your own failures.
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