Client
The client is a global leader in commercial real estate services, operating in over 100 countries with more than 140,000 employees. Its offerings span leasing, capital markets, valuation, project and investment management, covering four key segments: Advisory Services, Building Operations and Experience, Project Management (with Turner & Townsend), and Real Estate Investments.
To stay ahead in a rapidly evolving industry, the company is expanding its tech-enabled services, integrating sustainability into its solutions, and leveraging data-driven insights to help clients navigate complex real estate challenges with agility and innovation.
Market Trends in Commercial Real Estate
The commercial real estate sector is experiencing rapid shifts driven by hybrid work models, increased sustainability demands, and the need for data-driven decision-making. Industry leaders are investing in intelligent automation and advanced AI capabilities to enhance operational efficiency, scale services, and deliver superior client experiences. Achieving this at an enterprise level requires robust agent orchestration, secure integration, and effective cost governance to remain competitive and compliant.
Business Challenges
The COO to modernize operations by deploying scalable agentic AI systems capable of orchestrating tasks dynamically across diverse data sources such as SharePoint, ADO, and GitHub. However, several architectural challenges hindered progress:
- Fragmented governance and redundant code across multiple applications
- Limited scalability and absence of centralized moderation
- Lack of token-level financial operations, auditability, and comprehensive AI testing frameworks
- Incompatibility with open-source frameworks, restricting innovation
- Slow time-to-market for new agents due to inefficient deployment processes
Key objectives
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Establish centralized governance and monitoring for the entire agent lifecycle and cost tracking
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Enable dynamic orchestration of agents across real-time and static data sources
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Integrate seamlessly with internal systems and support open-source frameworks
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Implement robust AI testing and evaluation mechanisms
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Reduce time-to-market through reusable components and streamlined deployment
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Ensure secure access and global compliance through role-based access control (RBAC)
LTIMindtree Solution
LTIMindtree addressed these challenges with a comprehensive, modular solution anchored in its proprietary BlueVerse Foundry framework. This strategy provided a scalable architecture for dynamic orchestration, secure governance, and accelerated agent deployment.
Key solution components:
Deep discovery and strategic alignment
Modular orchestration and integration
Governance and cost transparency
Accelerated agent development and deployment
Enterprise-grade security and compliance
Business Benefits
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Achieved a 50 percent reduction in time-to-market for AI-enabled applications by leveraging reusable agent templates and centralized orchestration
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Improved operational efficiency by automating agent workflows and minimizing manual intervention across JIRA, ADO, and GitHub
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Provided secure, scalable access for over 10,000 associates through RBAC
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Enhanced governance and cost control via integrated FinOps, audit, and moderation capabilities within BlueVerse Foundry
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Accelerated deployment through dynamic configuration of real-time and static data connectors, eliminating redundant development work
Conclusion
LTIMindtree’s engagement with the client marks a significant step forward in scalable, secure, and intelligent AI agent deployment. By leveraging BlueVerse Foundry, the organization has established a robust foundation for dynamic orchestration, centralized governance, and seamless integration with enterprise systems.
This initiative has streamlined agent workflows, strengthened cost governance, and reduced time-to-market for new AI capabilities. Looking ahead, opportunities include expanding the Agent Marketplace, enhancing AI evaluation frameworks, and scaling use cases across business units to sustain enterprise-wide digital transformation.
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