Case Study
Stabilizing Delivery and Driving Modern Engineering for a Global EdTech Provider
Key Result Highlights
- Scaled to 150+ team members, tracking toward a 200+ team by Mar’26.
- Delivered strong customer satisfaction metrics with a CSAT of 5 and NPS of 9.
- Enabled modern engineering adoption, improving DORA metrics across teams.
- Supported 9+ customer platforms with consistent, predictable delivery.
- Maintained preferred-partner status for more than 3 years due to disciplined execution and continuous value addition.
The Client
The client is a tech-enabled education services organization with a
4,300-person global workforce. The company is a national leader in digital learning content, software, assessments, analytics, and simulations, serving licensure-driven and high-growth professional fields.
The Challenge
The client struggled with declining delivery quality and vendor complacency. Prior partners focused on transactional tasks instead of product and organizational impact, offered limited transparency, and lacked a strong governance model. These issues disrupted project flow, slowed execution, and prevented the organization from scaling modern engineering practices.
Critical Success Parameters
- Assemble a skilled, accountable team capable of rapid onboarding.
- Establish a governance model that ensures transparency, velocity, and
predictable delivery. - Blend onshore/offshore teams to improve collaboration and coverage.
- Adopt modern engineering practices to improve quality and speed.
- Reduce onboarding friction with a strong knowledge-transfer strategy.
- Drive continuous improvement instead of static, transactional
engagement.
Our Approach
- Built a specialized, high-performance staff-augmentation team aligned to modern engineering standards.
- Achieved rapid ramp-up within two to three months, supported by a structured KT plan.
- Combined offshore execution strength with onshore leadership and collaboration.
- Introduced Domain-Driven Design (DDD), Shift-Left practices, Test-Driven Development (TDD), and end-to-end CI/CD pipelines.
- Embedded continuous monitoring, efficiency tracking, and optimization to improve delivery flow.
- Implemented a governance model emphasizing accountability, transparency, and measurable outcomes.
- Positioned the partnership for upcoming AI Engineering initiatives beginning next month.
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