How Movate Built an AI Pod for SDLC Automation with Lyzr

Unified SDLC automation

Context-aware engineering

Centralized AI pod

About the company
Movate is a global technology services and engineering firm managing a large, distributed software development ecosystem. Their teams work across Jira, GitHub, SharePoint, TestRail, and Rally, handling high-volume releases, complex dependencies, and extensive QA cycles. As workloads grew, fragmentation across systems made consistency and velocity difficult to maintain.

The problem statement

Engineering teams had to manually trace dependencies across multiple systems to understand the impact of code changes. This slowed reviews and introduced risks across services, APIs, and test cases.

QA teams spent hours turning user stories into test cases. Incomplete context and scattered information made the process inconsistent and heavily manual.

Requirements, code, documents, and tests lived in different platforms. Teams struggled to form a unified view, slowing delivery and increasing the chance of misses.

Unified knowledge graph
Impact analysis agent
Test case generator
Code intelligence agent
Manager agent layer

The outcome

25–35% faster impact checks, 30–40% quicker test preparation, and consistent code patterns enforced automatically.

A shared knowledge graph replaced scattered data, reducing duplicated work and improving alignment across engineering and QA.

OAuth-based authentication, role-based access, complete audit trails, and private AWS connectivity ensured secure, controlled automation at scale.

The outcome

Behind the scenes: How Lyzr builds enterprise AI on AWS

Behind the Scenes: How Lyzr Builds Enterprise AI on AWS

How Lyzr handled security for a leading AI & automation research firm

Lyzr Agent Platform is SOC2, GDPR, and ISO 27001 compliant, ensuring enterprises can run their critical workloads safely.

The data resides within the customer's own cloud, ensuring100% ownership and adherence to data residency requirements.

Lyzr's reflection module reduces the chances of hallucination. This feature is enabled in most critical applications for higher accuracy.

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