6 real-world examples of companies getting results from AI with operations: the numbers, the companies, and the tools behind each win. Updated daily.
Most-used tools here: Amazon Quick, Amazon Bedrock AgentCore, Phaidra, NVIDIA DSX, NVIDIA NIM, Qatium
Phaidra applied self-learning AI agents built on NVIDIA DSX Flex, DSX Max-Q and DSX Exchange to tune cooling and power allocation in data centers. The result is roughly 10% more usable compute under the same power budget, plus better grid flexibility…
The nonprofit U.S. Hunger uses Amazon Quick, connected nightly to its SQL Server data via SPICE, so leaders can explore program and financial data without waiting on new data pulls. CEO Rick Whitted now follows his own questions through Full Cart…
Dell Technologies has spent close to two years running fully autonomous AI agents inside its own operations. The company argues that reorganizing people and processes around these agents, rather than just adding tools, is what gives it an edge. The article…
AWS describes a conversational workflow where supply chain managers ask Amazon Quick in plain language to spot disruptions, assess exposure, and draft an emergency RFQ. AgentCore-hosted MCP servers pull live data from ERP, monitoring, and procurement systems…
Eon, a cloud data platform vendor, used Amazon Bedrock AgentCore to build an MCP Gateway that replaces per-tool credentials and local MCP processes. Its engineers and autonomous SRE agent now reach investigation tools across AWS, GCP, and Azure through one…
Three startups from the Barcelona Supercomputing Center's AI Factory Accelerator Programme have moved AI into production or deployment. Qatium uses its water-network AI in early production, OneCareAI built a tool using NVIDIA NIM to flag hidden atrial…