Real teams. Real bugs. Real fixes.

The challenge

The team runs a high-traffic fashion marketplace across 14 markets. Their support team logged ~80 checkout-related tickets per week, but engineers could reproduce only 1 in 4. Triage stalled, refunds piled up, and a single broken Apple Pay flow in one country cost them an estimated six-figure sum in a single weekend before anyone could repro it.

What changed

They embedded the Oneclik widget into the checkout funnel and gave Tier-1 support a one-click report button inside the admin panel. Every ticket now arrives in Jira with the full DOM snapshot, console errors, network waterfall, and the user's locale, currency, and payment method.

The challenge

The KYC flow involves passport scans, address proofs, and selfie liveness checks. Internal QA was forbidden from sharing screenshots over chat - every bug report had to be manually anonymized, sometimes taking 30+ minutes per issue. The result: QA logged half as many bugs as they actually found.

What changed

Oneclik's automatic field redaction was configured to mask any element with sensitive data attributes. Console logs scrub auth tokens before they leave the browser. Reports route to a private Jira project with role-based access, and AI Summaries surface the user impact without exposing raw data.

The challenge

The insurer runs a claims portal used by adjusters and brokers across several European markets. When something broke mid-claim - a document upload that silently failed, a premium calculation that didn't match the quote - adjusters either worked around it or sent a vague email hours later. Reports often included screenshots with policy numbers, names, and IBANs, which compliance had to manually scrub before engineering could even look.

What changed

They embedded a floating Oneclik button into the claims portal and broker workbench. Adjusters click once, add a short note, and a fully redacted report - no names, no policy numbers, no IBANs, no claim amounts - lands in Jira. AI Summaries translate insurance terminology into engineering tickets, with the affected product line and country auto-tagged.

The challenge

The platform serves K-12 students on Chromebooks across several districts. When a quiz wouldn't submit or a video stopped buffering, students just gave up. Teachers occasionally relayed complaints to admins, who relayed them to support - losing all technical context along the way. The product team essentially flew blind on UX bugs.

What changed

They built a 'Something not working?' button into every lesson player. Reports include the lesson ID, browser, network throttling state, and last 30 console events. AI Summaries cluster reports by root cause, so the team sees '47 students hit the same video player race condition this week' instead of 47 individual tickets.

The challenge

The provider streams live and on-demand content across web, iOS, Android, and smart TV apps. When a CDN edge or DRM license server hiccupped, social channels filled with vague reports - 'video won't play,' 'stuck on loading.' Engineers spent hours figuring out which app version, which device, which region, and which stream the viewer was on. Some incidents lingered through prime time.

What changed

The team embedded Oneclik directly into each player surface. A single tap on the 'Report a problem' button captures the app build, device model, network type, CDN edge, DRM session ID, last 60 seconds of player logs, and a thumbnail. Reports auto-route by severity into PagerDuty, with AI clustering identifying the most-impacted region or title within minutes.