A leading global payments technology company needed a practical way to deploy AI agents across regulated business domains without sacrificing control, transparency, or reliability. The organization partnered with Grid Dynamics to implement a production-safe agentic AI platform that standardizes how agents are built, orchestrated, and monitored across functions such as finance, HR, supply chain, sales, and operations, with a focus on multi-agent enterprise workflows rather than isolated pilots.
Download to see how the platform design, shared services, and orchestration patterns make multi-agent enterprise workflows production-ready at scale.
The solution centers on an enterprise agentic AI platform that provides shared RAG services, guardrails, observability, and agent-to-agent coordination, powered by durable workflow orchestration on Temporal. This foundation supports use cases like Supplier 360, Customer 360, interview assistance, analytics and presentation generation, and conversational access to enterprise data. Rather than redesigning every process, the platform makes existing workflows faster, more consistent, and fully auditable, with human-in-the-loop controls where required.
To ensure repeatable outcomes, the team established a structured pipeline from business requirements through solution design, model selection, engineering, testing, and rollout. New use cases can move from concept to production in roughly three months, with built-in cost and latency optimization to keep AI operations sustainable. Early outcomes include an estimated 9–14 million dollars in annual savings and a reduction in analysis cycles from 4–6 weeks to a few hours, along with improved procurement efficiency, unified customer views, better recruiter productivity, and faster decision-making.
Download the case study for a deeper look at the architecture, governance model, and delivery process behind this platform for trusted multi-agent enterprise workflows.
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