ScaleOps has expanded its cloud resource management platform with a new product aimed at enterprises operating self-hosted large language models (LLMs) and GPU-based AI applications. The AI Infra Product announced today, extends the company’s existing automation capabilities to address a growing need for efficient GPU utilization, predictable performance, and reduced operational burden in large-scale AI deployments. The company said the system is already running in enterprise production environments and delivering major efficiency gains for early adopters, reducing GPU costs by between 50% and 70%, according to the company. The company does not publicly list enterprise pricing for this solution and instead invites interested customers to receive a custom quote based on their operation si [...]
Enterprise AI has a new infrastructure problem: companies are accumulating agents faster than they are developing systems to govern them.Gartner estimates that the average global Fortune 500 company w [...]
Enterprises can't fix their GPU waste problem because the fix makes the problem worse. Releasing idle capacity would improve utilization, but the same shortage driving GPU prices up is exactly wh [...]
Enterprise AI has largely been built around context engineering. Teams connect enterprise systems, generate chunks and embeddings, build retrieval pipelines, and assemble the context needed by individ [...]
Our LLM API bill was growing 30% month-over-month. Traffic was increasing, but not that fast. When I analyzed our query logs, I found the real problem: Users ask the same questions in different ways.& [...]
The New York and Israel-based startup, founded by a former Run:ai engineer and professional triathlete, has grown 350%+ year-on-year and counts Adobe, Wiz, DocuSign, and Salesforce among its customers [...]
Perplexity, the AI-powered search company valued at $20 billion, announced on Wednesday at its inaugural Ask 2026 developer conference that its multi-model AI agent, Computer, is now available to ente [...]
For the last 24 months, one narrative justified every over-provisioned data center and bloated IT budget: the GPU scramble. Silicon was the new oil, and H100s traded like contraband. Reserve capacity [...]
Across 107 enterprises, AI infrastructure spending is accelerating well ahead of the ability to see or steer its economics. Most organizations run their AI on a familiar base of hyperscalers and model [...]