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Episode 9 - AI, Enterprises, and the Law

In this episode of The Intelligent Enterprise, host Tom Stoneman takes us inside the different ways that AI is being utilized in the practice of law. In this episode, Tom is joined by Vintee Mishra, an attorney who’s currently part of the Commercial Contracting Organization at Navy Federal Credit Union, and has previously occupied supporting roles at Tata Consultancy Services, Cisco, First Technology Credit Union, and Moody’s Analytics.

What Native Audio in AI Video Actually Means for the Future of Content

In 2026, the arrival of native audio has officially ended the silent film era of generative AI. For years, creators had to hunt for sound effects and manually align voiceovers in post-production, but the new standard is simultaneous generation. Native audio means the AI no longer simply adds sound to a finished clip. Instead, models like Seedance 2.0 on the Higgsfield platform generate audio and video together in a single mathematical pass. This shift from fragmented tools to a unified multimodal architecture is fundamentally changing how content is produced.

Why Face Swap Is the Smartest Way to A/B Test Visual Creatives Without a Reshoot

A/B testing has always been a cornerstone of performance marketing. Marketers test headlines, tweak CTAs, adjust layouts, and refine copy continuously. These changes are easy to implement and quick to evaluate. Over time, even small improvements compound into measurable gains. But visual creatives have always been different. They are harder to test, slower to produce, and significantly more expensive to iterate. As a result, one of the most influential elements in a campaign often goes under-tested.

Responsible AI Writing: How Teams Use AI Tools Without Losing Authenticity

AI writing tools have made content creation significantly faster. Drafts that once required hours can now be produced in minutes, helping teams scale documentation, communication, and content production. However, speed alone does not guarantee quality. As AI-generated content becomes more common, many teams are finding that raw output often lacks clarity, consistency, or the tone required for professional use.

How Modern IT Solutions Secure Business Operations and Drive Scalability

In today's fast-paced digital economy, business growth is heavily dependent on technological capability. However, as organisations expand their digital footprint, they simultaneously widen their attack surface. Scaling operations without a robust security framework often leaves companies vulnerable to severe operational disruptions, regulatory fines, and reputational damage. For business leaders, the challenge lies in deploying infrastructure that supports rapid growth while maintaining airtight security across all digital assets.

Why Autonomous AI Agents Can't Run on SaaS Infrastructure

The era of the “copilot” is ending. We are moving rapidly toward the era of the autonomous software factory, where autonomous agents don’t just autocomplete our code—they investigate, plan, test, and merge entire features while we sleep. But this shift has exposed a critical flaw in how we consume AI. For the past decade, the default motion for enterprise software has been SaaS. It’s easy, frictionless, and managed by someone else.

How AI Is Powering the Next Era of IT Operations

AI is redefining the future of IT. In this Nexus Live 2025 keynote, ScienceLogic CEO and Founder Dave Link shares the vision behind Skylar AI, why the industry is shifting toward autonomous operations, and how organizations can move faster, smarter, and more proactively than ever before. In this session you’ll see.

LLM Cost Monitoring with OpenTelemetry

Teams running LLM applications in production face a cost problem that traditional APM tools were never designed to solve. CPU and memory costs are relatively predictable — a web service processing 1,000 requests per second costs roughly the same week over week. LLM API costs are not. A single user session can cost $0.01 or $5 depending on prompt length, model choice, conversation history, and how many retries happen inside your chain.

How to Catch AI Code Mistakes Before They Reach Production

AI can write code fast, but it makes mistakes humans often don't. In this session from Ole Lensmar, CTO of Testkube, breaks down the real quality risks of AI-generated code and how engineering teams can build guardrails before those bugs hit production. What you'll learn: Common mistakes LLMs make (and which ones are unique to AI) Whether you're a developer leaning on AI to ship faster or a QA lead trying to keep up with the pace of AI-generated code, this talk gives you a practical framework for staying ahead of quality issues.