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CASE STUDY | TECHNOLOGY

EV charging technology provider cuts regression time by 90% with AI-driven managed QA services

Agile portfolio evolution

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The Client

A U.S.-based electric mobility technology provider supporting large-scale EV charging deployments across residential, commercial, and enterprise environments.

The Situation

When rapid innovation in electrification exposes the limits of a legacy QA model

As the client expanded its EV charging technology ecosystem, its digital platforms became increasingly central to customer experience, partner integrations, and operational performance. New features and rising demand increased expectations for faster, more reliable releases—but QA hadn’t evolved at the same pace. Testing remained largely manual within a staff-based model that limited scalability and strategic value, while limited Agile alignment made in-sprint validation difficult and regression cycles longer as complexity grew.

With contracts up for renewal and growth continuing, it became clear that simply adding more testers wouldn’t be enough. QA needed to shift from execution support to an automation-driven, managed capability aligned with Agile delivery and business expansion.

The Solution

Service overview

AI-augmented managed QA services transforming manual testing into intelligent, automation-first quality engineering embedded within CI/CD pipelines and Agile delivery cycles.

Approach

Validated intelligent test automation through a rapid proof of concept, then transitioned to a managed QA model embedded within Agile pods. Integrated automation into Azure DevOps to enable in-sprint validation and continuous regression execution.

Key actions
  1. Executed a PoC to validate automation feasibility across core platforms.
  2. Built and scaled an automated regression suite across browsers and devices.
  3. Integrated automated test execution into Azure DevOps CI/CD workflows.
  4. Enabled in-sprint test case creation and automation within Agile pods.
  5. Expanded regression coverage to support rapid feature releases.

Driving Results

  • Cut regression cycle time by 90%, from 5 days to 12 hours.
  • Achieved 90%+ automated regression coverage.
  • Identified 99%+ of defects pre-production.
  • Delivered 900+ automated test scripts and detected 2,200+ defects.
  • Embedded QA within Agile pods, enabling true shift-left validation.
  • Scaled testing capacity to support 50+ feature releases without increasing delivery risk

Bottom line

We make AI-driven managed QA services for electrification and EV infrastructure platforms Simple, Smart, Reliable—turning quality into a growth enabler, not a bottleneck.

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