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About the Client
Our client is a global leader in travel technology, providing advanced solutions for payments, airlines, airports, hotels, railways, cruise liners, and more. The client is headquartered in Europe, operates in over 190 countries, employs more than 20,000 people globally, and reported $6.9 billion in revenue in 2025. They serve over 2 billion passengers annually and maintain an extensive portfolio of more than 1.1 million B2B clients.
Racing Toward Digital Transformation in Travel Tech
In the rapidly evolving travel industry, customers increasingly expect faster, personalized, and seamless experiences. This shift is driving widespread digital transformation, leading to the greater adoption of mobile and app-based technologies, advancements in artificial intelligence, and a growing focus on sustainable tourism. To stay competitive, travel tech companies must accelerate innovation, modernize their platforms, and maintain cost-efficiency.
In this competitive landscape, the client faced immense pressure to:
- Deliver faster releases across its existing multi-cloud Salesforce environments
- Maintain high development standards across global teams
- Reduce technical debt and improve test coverage
- Make Manual development and impact analysis processes agile and scalable
The client recognized the strategic importance of embedding AI into its Salesforce development lifecycle to maintain a competitive edge.
Strategic Goals to Future-Proof Salesforce Development
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Implement AI-driven Salesforce development to improve speed, quality, and consistency
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Shift impact analysis left into story development
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Improve code and test coverage
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Simplify development and reduce manual effort
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Deliver faster to market with fewer defects
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Why Traditional Development No Longer Suffices
Despite having a large Salesforce ecosystem, our client struggled with slow delivery timelines, inconsistent development practices, and limited test coverage. Manual impact analysis consumed nearly 20% of the overall effort, while fragmented workflows contributed to prolonged development cycles. As Salesforce expanded across business units, the traditional development model proved increasingly unsustainable, highlighting the need for a more innovative, smarter, and streamlined approach.
Challenges
- Lacked AI-driven Salesforce development that can accelerate delivery without compromising speed, quality, and consistency
- Impact analysis was time-consuming and took up to 20% of the total effort.
- Development standards were inconsistent and varied across teams and regions.
- Development time was longer and accounted for 60% of the total effort, delaying releases
- Testing coverage was limited, which increased the risk of defects and rework. Further, it made it harder to simplify development, improve code quality, and deliver faster to market
LTIMindtree solution
To help our client achieve their strategic goals of accelerating delivery, enhancing quality, and standardizing Salesforce development, we implemented a tailored, AI-augmented development framework optimized for both AM (Application Management) and AD (Application Development) environments.
Key features
Prompt-driven development
AI-assisted generation of LWC, Apex Classes, Triggers, Flows, and debugging scripts
Shift-left impact analysis
Embedded into story development using AI to identify dependencies early.
Consistent standards
Enforced through AI-generated templates and reusable components.
Automated test coverage
AI-generated test classes and scenarios to improve coverage.
Technical debt identification
Proactive detection and flagging of code inefficiencies.
Zero copy integration
Secure, environment-specific development using AgentForce, Co-Pilot, and Results Verification tools
Each capability was mapped directly to the challenges—reducing manual effort, improving quality, and accelerating delivery.
Business benefits
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25% reduction in development time
in the first month
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50% reduction in analysis effort
in the first month
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30% (Dev) and 60% (Analysis) effort reduction
from month 5 onward
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40% total efficiency improvement
from month 5 onward
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Improved code quality and test coverage
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Faster time-to-market
with fewer defects and rework
Strategic Execution Plan
LTIMindtree Interactive followed a 5-step roadmap to guide the organization in this talent acquisition framework:
- Strategic alignment: Synchronized with leadership and key stakeholders.
- Opportunity list creation: Identified quick-win opportunities and long-term strategic goals.
- Exploring market options: Evaluated current talent acquisition technologies and identified the best-fit tools.
- Proof of concept: Piloted next-gen AI applications for talent acquisition such as generative AI for job descriptions and candidate outreach.
- Execution: Developed a detailed implementation timeline, prioritizing high-impact areas first.
Tech stack
Salesforce Lightning (LWC, Apex, Flows), AgentForce, Co-Pilot, Salesforce DX, GitHub, Bitbucket, Jenkins, GitLab CI
— Katie Li, Senior Director - Practice Sales, LTIMindtree
Future of AI Agents: Scaling Innovation in Salesforce
The client’s adoption of AI-augmented development marks a pivotal shift in how enterprise Salesforce environments are managed. With automation, intelligent impact analysis, and consistent standards, the client is now positioned to scale development globally, reduce rework, and accelerate innovation across its travel tech ecosystem. Future enhancements include self-learning models, predictive refactoring, and autonomous code optimization.
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