Our Client

The client is a leading global travel technology provider whose platforms support more than 1.1 million businesses across the travel ecosystem and process billions of transactions annually. Salesforce serves as the foundation for customer engagement and commercial operations, supporting more than 10,500 users across the enterprise.

As software demand accelerated across the enterprise, engineering teams needed to scale delivery without increasing complexity. Existing development workflows relied heavily on manual effort and fragmented validation processes, making it increasingly difficult to sustain delivery velocity while meeting enterprise governance standards despite continued investments in Salesforce Development Services.

Key Challenges

As Salesforce delivery programs expanded, engineering teams struggled to keep pace with growing release volumes while maintaining quality, security, and governance. Ticket analysis, code validation, testing, and deployment relied heavily on manual effort, slowing delivery and limiting engineering productivity. These limitations became particularly visible during one major release, where repeated validation failures delayed production deployment for nearly 10 days, exposing the limitations of traditional debugging approaches.

To modernize software engineering, the organization needed to:

• Accelerate engineering throughput without increasing headcount
• Reduce manual effort across the Salesforce SDLC
• Improve software quality while minimizing defects and technical debt
• Embed governance, security, and compliance into AI-assisted engineering
• Establish a scalable, enterprise-ready delivery model for future Salesforce programs

LTM’s Solution

LTM designed and implemented Agentic Engineering in Salesforce (AgEiS), an enterprise-governed AI framework orchestrated on the LTM BlueVerse Platform that augments the complete Salesforce software development lifecycle.

At the core of the platform are 42 specialized AI agents, intelligent orchestration, and AI Council governance that collectively support ticket analysis, code generation, quality validation, testing, deployment, and compliance verification while maintaining enterprise-grade auditability and security. This approach modernized AI-Powered Salesforce Development by combining intelligent automation with human oversight across the engineering lifecycle.

Key capabilities included:

• AI-assisted ticket analysis, solution design, development, testing, and deployment across the Salesforce SDLC
• Intelligent orchestration using specialized AI agents to automate engineering workflows while keeping developers in control
• Governance-by-design with embedded security, compliance, auditability, and enterprise quality controls
• Continuous validation that reduced defects, minimized technical debt, and improved delivery predictability
• A reusable enterprise architecture supporting governed AI adoption across multiple Salesforce programs

The platform consistently translated AI into measurable engineering outcomes. During one production deployment, AgEiS identified and resolved 12 complex validation failures in just 30 minutes after nearly 10 days of manual troubleshooting, enabling a zero-error validation cycle and successful same-day deployment.

This engagement reflects Business Creativity in action, where deep Salesforce engineering expertise, governed Agentic AI, and enterprise-scale orchestration came together to transform software delivery into an intelligent operating capability. Rather than automating isolated engineering tasks, LTM established a reusable operating model where AI continuously augments engineering decisions across the Salesforce SDLC, enabling governed software delivery at enterprise scale and redefining how enterprises approach Salesforce Development Services.

Business Outcomes

The transformation delivered measurable business value across engineering operations:

• Increased delivery throughput by 30%, from approximately 157 to more than 200 user stories per month
• Improved engineering efficiency by 49%+ per FTE, enabling greater output without increasing headcount
• Reduced ticket analysis effort by 75%, cutting effort from 32 hours to 8 hours
• Accelerated development cycles by approximately 50%
• Reduced software defects by approximately 60%
• Lowered technical debt by approximately 90%
• Generated more than €350K in annual productivity savings
• Established an enterprise-governed AI operating model approved through client AI governance and security processes

Conclusion

By establishing AgEiS as a reusable enterprise capability, LTM equipped the client to scale governed AI beyond individual development teams and across future Salesforce transformation programs. As engineering complexity continues to grow, the platform provides a trusted foundation for accelerating innovation, strengthening governance, and enabling AI-assisted software delivery at enterprise scale. This transformation demonstrates how AI-Powered Salesforce Development enables organizations to modernize engineering while delivering secure, scalable, and business-driven outcomes.


Please reach out to Pradeep.Indiresh@ltm.com to learn more and schedule a personalized session for your organization.