TL;DR: TaloTrace, an AI-powered QA testing platform, hides new findings by default because they haven't been reviewed yet: it verifies each finding independently before it reaches you, then keeps results invisible to the wider team until a reviewer approves them, or your project is set to auto-approve. It's a deliberate gate, not a bug, and you can configure it to move faster.
Key Takeaways
Fail-closed by default: every run's findings start hidden until a reviewer approves them or auto-approve is switched on for that project.
Two separate checks: TaloTrace independently verifies a finding before it reaches the queue; the visibility gate is a later, separate step your team controls.
Low-confidence findings need individual sign-off: they're held apart from the rest and cannot be released in bulk by a run-level approval.
Ticket export waits too: Jira, Linear and GitHub export only happens after a finding has passed review, and only if your project has export switched on.
You choose the speed: auto-approve is a per-project setting, so the gate is a default you can loosen, not a fixed rule.
Notifications close the loop: in-app and email alerts fire when a run publishes or a finding is waiting on a reviewer.
Why Does This Even Need Asking?
If your QA tool ran a test and found a bug, the instinct is to want to see it straight away. When results sit behind an approval step instead, it can read as a bottleneck, something standing between a real problem and the engineer who needs to fix it.
TaloTrace hides results by default for a specific reason: a finding that hasn't been checked is a claim, not a fact. Showing every claim to the whole team the moment it appears trades a few minutes of waiting for a queue full of noise that engineers learn to ignore. The gate exists to keep what reaches your team worth acting on.
Why Does Every Run Start Hidden, By Design?
Fail-closed visibility is the practice of hiding new findings by default until they're explicitly reviewed and released, rather than showing every raw detection the moment it's produced.
Every run TaloTrace completes starts with its findings hidden. They become visible to the wider team only when a reviewer approves them, or when the project has been explicitly configured to auto-approve. That second option matters: hiding results is the default, not a fixed rule you can't change.
Low-confidence findings get extra caution. They're held apart from everything else, and a run-level approval can't sweep them into visibility in bulk. Releasing one takes an explicit, per-finding decision, so a weak signal doesn't reach engineering just because the rest of the run looked clean.
Who Decides What You See, and How?
Before a finding ever reaches that hidden queue, TaloTrace has already checked it once. It explores your app on its own, without scripts to maintain, the way we cover in our guide to autonomous mobile app testing, and independently verifies each finding before it reaches you. Nothing you see is the raw, unchecked output of the step that produced it.
The approval gate is a second, separate layer on top of that. It's the point where a person on your team, or an auto-approve setting you chose, decides whether a verified finding is ready for the rest of the team to see. TaloTrace backs that decision with evidence rather than asking anyone to take its word for it: a screen recording is captured for every run, each finding carries the time window inside that recording where the defect shows, and a vision model examines the recording for visual and functional anomalies, not only hard failures.
What Lands in Your Queue Once a Finding Is Approved?
An approved finding isn't a one-line alert. It comes with a recording, TaloTrace's reasoning, and a step-by-step reproduction in the Evidence panel, so a reviewer or an engineer can see exactly what happened without rerunning the scenario themselves.
Severity travels with it too. TaloTrace rates findings across five levels, Critical, High, Medium, Low and Trivial, shown alongside their internal P0 to P4 code, so a tile can read "Critical (P0)" at a glance. If you've given TaloTrace your own severity-rating guidance, it rates against that guidance as well.
You're not left guessing when something needs your attention. Notifications go out through an in-app feed with durable history and by email, firing when proposed scenarios are ready to review, when a run's results publish, and when a finding is waiting on a reviewer.
Export to Jira, Linear or GitHub follows the same gate. It's configured per project and off by default, and a finding can only be exported after it has passed review, so nothing lands in an external tracker unverified. Export is idempotent too: a finding that's already been filed gets commented on rather than opened twice.
Where Does Fail-Closed Visibility Stop?
The gate only controls visibility, not whether tests run. It doesn't decide when a scan happens or which scenarios execute; that's set separately, on demand or on a recurring schedule, and it runs the same credit check either way.
Auto-approve removes the human step, but someone still has to switch it on deliberately. Until they do, results wait on a person to look at them, and if no one is checking the queue, findings simply stay hidden. Low-confidence findings raise that bar further: holding them out of bulk approval on purpose means they need individual attention rather than a quick sweep.
What Makes TaloTrace's Approval Gate Different?
The two layers are what set this apart from a tool that just prints whatever a single automated pass produced. TaloTrace's independent verification happens before a finding is even eligible to sit in the hidden queue, and the fail-closed default means an unverified item has no route to your whole team's attention by accident. TaloTrace's site reports up to 90% reduction in QA spend, reported by early teams, and 4x more validated bugs surfaced compared to manual QA.
You still control the trade-off. If a low-stakes project calls for speed, auto-approve gets findings to you as soon as TaloTrace's own check clears them. If you want a second set of eyes before anything reaches the wider team, the default fail-closed behaviour gives you that without extra configuration. The full path from a stated goal to a finding in your queue is covered in how TaloTrace works.
Frequently Asked Questions
Can we turn off the approval step and see results immediately?
Yes. The fail-closed gate is a per-project default, not a fixed rule. You can configure a project to auto-approve, and findings become visible as soon as TaloTrace's own independent check clears them, without waiting on a person to sign off.
Who is the 'someone' that has to approve a finding?
A reviewer on your team, working through your project's queue in TaloTrace. It isn't TaloTrace waiting on a second pass of its own; the independent verification TaloTrace performs already happened before the finding reached that queue.
What happens to low-confidence findings?
They're held apart from the rest of a run's results and can't be released in bulk. Approving the run doesn't sweep them into visibility automatically, each one needs its own explicit decision, which keeps a weak signal from reaching engineering by accident.
Does the approval step delay tickets going into Jira or Linear?
Yes, by design. Export to Jira, Linear or GitHub only happens after a finding has passed review, and only if your project has export switched on, since it's off by default. Nothing reaches an external tracker unverified.
How do we know when something is waiting on us?
TaloTrace sends notifications through an in-app feed with durable history and by email. They fire when proposed scenarios are ready to review, when a run's results publish, and when a finding is waiting on a reviewer.
Seeing This on Your Own App
If you want to walk through the approval queue and the Evidence panel against your own app, apply for early access and see it running there directly. Plan details, including which device profiles each tier unlocks, are on the pricing page.
