In high-frequency trading environments, visual clarity is a must-have. One digital-first investment platform with over two million users learnt it the hard way when its UI quality was becoming more difficult to maintain as the team scaled.

Each weekly release introduced new components, layout variations, and design tweaks. But without a visual testing layer in place, small regressions often slipped into production. Charts would shift. Buttons would overlap. Colors would break under dark mode.

These inconsistencies started affecting investor confidence and increasing customer support volumes.

To solve the problem, the platform adopted TestGrid’s AI-powered visual testing capabilities, integrated directly into their existing automation workflows. This allowed them to systematically detect, analyze, and resolve visual bugs early in the SDLC.

The Challenge: Visual Bugs Slipping Through Standard Automation

The platform’s QA process was already mature in terms of functional coverage. Automated tests verified data flows, API responses, and basic UI interactions. But there was no reliable method to validate how the interface looked across devices, browsers, and resolutions.

As the product team rolled out new dashboards, dark mode themes, and region-specific UI elements, visual inconsistencies began to appear.

These included:

• Misaligned charts on tablets and smaller screens
• Overlapping buttons and clipped labels in certain browsers
• Color rendering issues that impacted dark mode readability
• Inconsistent spacing and layout shifts during localization rollouts Since these changes didn’t break functionality, they often went undetected during test cycles. Bugs were discovered only after users flagged them, typically during high-traffic events like earnings season or product launches.

The QA team needed a way to monitor the visual layer of the application without disrupting the existing automation pipeline or adding maintenance overhead.

The Solution: Built-In Visual Testing with AI-Powered Precision
To strengthen their testing coverage, the platform adopted TestGrid’s AI-powered visual testing without introducing new tools or changing how their teams worked.

They integrated visual testing directly into their existing automation scripts using a few lines of configuration. No external SDKs were required, and there was no need to rewrite test cases. Visual comparisons were automatically triggered during CI runs, comparing current UI states with approved baselines.

Here’s what they implemented:

• Visual AI for baseline comparison, detecting layout shifts, font changes, missing elements, and pixel deviations
• Parallel testing across real devices and browsers, ensuring consistency across all supported environments
• Threshold configuration, allowing teams to control sensitivity and ignore non-critical changes like dynamic timestamps
• Centralized reporting, so teams could review flagged issues with screenshot comparisons and approve or reject changes
• The rollout was completed incrementally across web and mobile teams, starting with high-traffic modules like dashboards and transaction flows. Within two sprints, visual issues that previously reached production were being caught and resolved earlier in the cycle.

The Results: Fewer UI Bugs, Faster Issue Resolution

Within one quarter of adopting TestGrid visual testing, the platform saw measurable improvements across QA and engineering teams.

Key outcomes included:

• 70% reduction in UI bugs reported post-release, based on internal issue tracking across three product lines
• Better alignment between design and engineering, as visual diffs made UI changes easier to track and verify
• Increased release confidence, especially for high-impact modules like portfolio dashboards and trade confirmations
• Faster triage of visual regressions, with automated screenshot comparisons helping teams identify and resolve discrepancies early
• Most importantly, the platform was able to maintain velocity without sacrificing quality. Visual testing became a natural part of the development cycle, not an added burden.

What the Client Had to Say

“Before TestGrid, visual issues were the hardest to catch and the slowest to fix. We had solid automation for functionality, but nothing for how things actually looked. Now, visual checks are baked into every release. It’s helped us reduce noise, align better with design, and ship with more confidence.” — Head of QA Automation, Digital Investment Platform

Why Visual Testing Matters for Complex, User-Facing Products

This case shows how visual quality can quietly become a liability as products grow in complexity. Functional tests can confirm that data is accurate and actions complete successfully. But they don’t catch layout shifts, broken styling, or inconsistent rendering.

For digital platforms where precision and trust go hand-in-hand, visual accuracy matters. Visual bugs may not break workflows, but they do affect perception, usability, and credibility.

With TestGrid’s built-in visual testing:

Developers get faster feedback with fewer surprises late in the cycle
QA teams gain visibility into UI changes across browsers and devices
Design and engineering stay aligned through visual comparison and approval workflows
Whether you’re supporting millions of users or preparing for scale, adding a visual layer to your test automation gives you more control over how quality is defined and delivered.

Ready to Strengthen Your UI Testing Workflow?

If your QA process already covers functionality but struggles with layout issues, missed visual regressions, or inconsistent user experience across devices, it may be time to add visual testing to your stack.

TestGrid makes it easy to get started:

• No SDKs to install
• No need to rewrite existing test cases
• Visual AI that integrates directly with your automation This blog is originally published at Testgrid : AI Visual Testing Helped This Investment App Boost QA Accuracy and User Confidence