Get the Case Study
How a Fortune 500 manufacturer enabled production-ready deep research agents
As AI agents move from experimentation to enterprise deployment, the real opportunity lies in scaling them with reliability, observability, and governance. A Fortune 500 global manufacturer operating more than 100 plants worldwide recognized this early and set out to turn decades of distributed knowledge into actionable intelligence with an enterprise deep research agent.
The company’s knowledge base spanned manufacturing, logistics, and supply chain domains but was scattered across systems, making it difficult for teams to find accurate insights in real time. They needed a way to connect this institutional knowledge and deliver trusted, cited answers instantly through an enterprise deep research agent.
See how enterprise deep research agents deliver trustworthy insights in seconds
Enterprise deep research agent platform foundations
Working with Grid Dynamics, the manufacturer built an agentic AI platform powered by Temporal, enabling durable orchestration, state management, and full lifecycle observability. The architecture introduced reusable agent templates, drag‑and‑drop workflow builders, and declarative retry logic so teams could focus on business logic, not infrastructure complexity.
Temporal’s enterprise-grade durable execution ensures every workflow step, from data retrieval to analysis, runs reliably and recovers seamlessly after interruptions. The platform’s Kubernetes‑based scalability allows new agents to spin up on demand, supporting long‑running, multi‑agent workloads with ease, a critical capability for enterprise AI adoption.
The results speak for themselves:
- 5,000 daily users, scaling toward 50,000+
- 90% faster access to enterprise intelligence
- 30–50% reduction in manual agent management effort
By deploying production‑safe enterprise deep research agents, the manufacturer unlocked reliable, governed, and scalable AI workflows, bringing precision, speed, and trust to every decision.
Explore the full case study to learn how your organization can operationalize Temporal‑powered deep research agents at scale.
Tags
You might also like
If you haven't realized that artificial intelligence is fundamentally reshaping business models, from the way we leverage technology for core operations to the rapidly increasing pace of change and innovation, it's beyond time to face the current reality. This new reality dictates: Adapt or fad...
To meet the need for faster deployments and a scalable, cost-efficient infrastructure, a leading global manufacturer of electronic components worked with us to reach those goals faster. They needed a modern application to track component lifecycles, demands, and delivery timelines, and calculate co...
In the current on-demand marketplace, customers dictate the rules of engagement. And with the rapid rate of cool new features becoming available, businesses need to be ever-present and just as rapid in development and delivery. Our client, one of the largest department store chains in the US, en...
See how a leading omnichannel sleep retailer used an AI retail search assistant to make online discovery feel as guided as an in-store consultation. In this case study, you’ll learn how Grid Dynamics designed a triage-first discovery platform that blends fast facet search with a conversational shop...
Delivering customer service at the speed of today’s expectations is not optional anymore. See how a leading automotive retailer restructured its e-commerce search and customer support by implementing a conversational AI agent on WhatsApp and achieved response times as fast as 3 seconds, enablin...
In the telecom industry, retaining customers is a survival strategy. Rising competition, customer dissatisfaction, and delayed churn detection often leave providers reacting too late. A global telecom giant partnered with Grid Dynamics to modernize its AI churn prevention system, transforming m...
A Fortune 500 wealth management firm partnered with Grid Dynamics to boost financial advisor productivity and accelerate decisions with two connected capabilities: a financial services AI copilot for rapid knowledge discovery and an AWS‑native reporting platform for fast, trusted metrics. In plain...

