Systems | Development | Analytics | API | Testing

Most enterprises have made the commitment to AI. They’ve approved the budgets, stood up the pilots, and named it a strategic priority. So why are 95% of them getting zero return on $30–40 billion in GenAI investment? According to MIT research cited in Hitachi Vantara’s 2025 State of Data Infrastructure Global Report — which surveyed more than 1,200 IT leaders across 15 markets — the failure isn’t the model. It’s the infrastructure underneath it.

Enterprise adoption of large language models introduces a fundamental security challenge: how do you grant AI agents access to internal data without creating a backdoor that bypasses your existing access controls? Traditional database connections rely on service accounts with broad permissions, but when an LLM queries your customer records or financial data on behalf of a user, it must respect that user's specific entitlements.

The rapid proliferation of Artificial Intelligence (AI) agents and Large Language Models (LLMs) is transforming how businesses operate. From automating customer service to generating complex reports, AI agents are becoming indispensable. However, this explosion of AI-driven interactions brings with it significant challenges in management, security, and governance.

Product teams tasked with providing an AI analytics and BI platform to finance organizations see a unique set of challenges. Finance organizations are subject to SOX, GDPR, EU AI Act compliance on top of accurately closing the books and preparing for the potential of an audit. In a highly regulated industry like finance, product leaders building solutions for finance leaders need accurate insights they can trust that hold up to audits and regulatory scrutiny.

Your AI agent just placed 47 duplicate orders. It called the wrong API three times in a row. It looped through the same workflow for six minutes before anyone noticed. Nobody caught it in testing because nobody built the right tests. That's not a hypothetical. Enterprises using AI agents face this exact problem every week. The AI agent works perfectly in staging, but fails silently in production, and by the time the on-call engineer gets alerted, real customers are already affected.

A financial services startup launched its AI assistant without doing a proper LLM testing checklist. Within 72 hours, it gave three customers dangerous advice, telling them to withdraw their retirement savings and invest in penny stocks. The problem? The advice was completely made up. There was no validation, no factual grounding, just confident and detailed responses that were entirely wrong. The company then spent the next six months addressing regulatory issues and rebuilding customer trust.

ClearML has announced native floating license management for NVIDIA AI Enterprise licenses with one-click deployment of NVIDIA NIM microservices across AI infrastructure. The feature, available now to ClearML enterprise customers, fundamentally changes how organizations consume NVIDIA AI Enterprise software licenses, moving from a static per-GPU assignment model to a dynamic pool that follows active workloads.

Government and defense agencies require extreme security measures to protect sensitive data like classified intelligence and military operations. Air-gapped systems, which are physically isolated from external networks, provide a robust solution by ensuring no remote access is possible. These systems are critical for deploying large language models (LLMs) safely in secure environments, enabling advanced AI capabilities like intelligence analysis and mission planning without risking data breaches.

Organizations over the years have seen the writing on the wall: The future is cloud. Now, these companies and their DevOps teams areevolving, innovating, and pursuing new technologies, to gain a competitive edge and create new efficiencies. One of the ways they’re doing this is through application migration to cloud. In this blog, I’ll detail the nuances of application migration and how to best manage data during it, including various challenges and their solutions.