Case Study

How UST modernized its own integration stack and built the foundation for enterprise-wide AI agent orchestration.

A legacy integration platform that took days per delivery. Replaced in 10 weeks with zero downtime and a new capability the whole enterprise now builds on.

A legacy integration platform that took days per delivery. Replaced in 10 weeks with zero downtime and a new capability the whole enterprise now builds on.
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OUR CLIENT

UST is a global technology services company with more than 35,000 people, operations across 30+ countries, and a client portfolio spanning financial services, healthcare, retail, and manufacturing. The organization runs entirely on cloud and SaaS applications. The integration layer keeping those applications connected had not kept pace.

As the application landscape moved entirely to the cloud and SaaS, the existing legacy integration platform became a business constraint. Extended development times and lack of observability meant even routine integrations could take days to deliver. At an organization operating at UST's pace, that lag time had a compounding cost.

THE CHALLENGE

A legacy integration layer that couldn't keep up with a cloud-first organization slowing every team that depended on it.

UST's application landscape had become entirely cloud-based and SaaS-driven. The integration platform connecting those applications had not evolved with it. The gap between what the business needed and what the integration layer could support was widening.

Four constraints were shaping the challenge:

  1. Delivery speed. Lack of visibility and extensive code changes resulted in lengthy development timelines. Business requests sat in a queue, and the platform couldn't clear fast enough.
  2. Platform mismatch. The legacy integration platform was designed for on-premise and hybrid environments. UST's infrastructure had moved entirely to cloud and SaaS, so the tooling no longer fit the architecture.
  3. Scalability ceiling. The legacy platform couldn't scale to support growing volumes of integrations, new systems, more complex orchestration patterns, or provide the agility required by the business.
  4. Skills accessibility. Specialized expertise that was increasingly difficult to resource and retain as the technology ecosystem moved toward low-code approaches.

The goal was not just a platform replacement, but a fundamental shift in how fast the organization could operate. UST needed a foundation capable of supporting what came next: agentic automation across the enterprise.

THE TRANSFORMATION

A two-phase approach: high-speed stack modernization, then AI-powered agent orchestration across the enterprise.

Phase 1 — Integration modernization at speed

After evaluating multiple modern integration platforms, UST selected Workato, not solely on features, but on three strategic criteria:

  1. The ability to scale with the organization
  2. A low-code approach accessible to a broader team
  3. A platform architecture that could support long-term innovation beyond point-to-point integration.

The migration design was deliberate. Rather than a high-risk big-bang cutover, the team delivered in weekly releases, allowing incremental validation, early issue resolution, and coordinated handoffs with third-party systems. A four-week evaluation phase upfront tested critical use cases and surfaced challenges before they became delivery risks.

The numbers tell the execution story:

One aspect of the delivery was particularly notable. At the outset, most of the UST IT team had limited Workato experience. Through the evaluation and delivery process, that changed. The team built deep expertise that extended well beyond the migration itself. What began as an internal implementation became an organizational capability trusted by UST clients.

The results were immediate. Development cycles that previously took days were reduced to hours. Operational visibility improved significantly, enabling a proactive shift-left approach to issue management. The platform now handles greater volumes, connects more systems, and can expand to new use cases without rebuilding.

Phase 2 — AI-powered agent orchestration

With the integration backbone in place, UST is extending the platform into its next phase: orchestrating AI-driven agents across the enterprise. Workato becomes not just an integration layer, but a coordination layer for autonomous workflows — connecting AI agents, enterprise systems, and human-facing processes at scale.

This is the architecture most enterprises are trying to reach: a governed, secure, and scalable backbone that can coordinate human and machine work across the organization without fragmentation or duplication. UST built it internally first — and is now deploying it for clients.

THE IMPACT

Immediate delivery gains, a scalable, and secure orchestration platform, and a new organizational capability the enterprise can build on.

Explore UST integration and automation capabilities → Workato