Getting a first computer vision deployment live is the easy part, so why do so many scaling programs stall?

In this conversation, we challenge the assumption that scaling is simply a matter of adding more cameras and sites. Instead, we explore what actually determines whether a program becomes a repeatable operational capability or gets stuck at use case one. Rather than focusing on theory, this discussion brings a practical, field-tested perspective on how leading organizations are sequencing rollout, aligning stakeholders, and building governance structures that hold up under real-world pressure.

We unpack the three layers that separate a deployment that scales from one that doesn’t: the model, the logic, and the operational layer. Through concrete examples and candid insights, this webinar will reframe how you think about implementation, helping you move beyond the first use case and toward a rollout motion that gets faster, not harder, with every new camera, site, and workflow you add.

Union resistance is often seen as one of the biggest barriers to scaling computer vision, but what if that assumption is wrong?

In this session, we challenge the “fear factor” and explore how unions and workforces are increasingly engaging with AI-driven initiatives when they are introduced with the right intent, structure, and safeguards. Rather than focusing on theory, this discussion brings a practical, real-world perspective on how leading organizations are approaching deployment in a way that builds trust from day one.

We unpack what truly drives acceptance on the ground, from transparency and governance to aligning technology with worker benefits. Through concrete examples and candid insights, this webinar will reframe how you think about adoption, helping you move beyond hesitation and toward scalable, responsible implementation.

In the first session of In Plain Sight, we tackle the critical question: how do you scale computer vision without creating complexity? This masterclass explores the shift from simple detection to true operational foresight. It challenges the idea that scaling has to be slow, heavy, or disruptive and shows how it can be structured, fast, and value-driven from the start.

Through real-world examples from safety, quality, and operations, the session breaks down what actually happens after the first successful use case. Why do some rollouts gain momentum while others stall? What causes alert fatigue? And how do you expand across sites without losing control? The conversation surfaces the practical decisions that separate pilot projects from scalable programmes.

Built for operations, safety, and industrial leaders, this webinar delivers clear thinking, sharp insights, and a practical framework for growth. If you want to move beyond isolated wins and build a computer vision strategy that compounds value over time, this session sets the foundation.

Vision to Decision Part 2 is for safety and operations leaders who know AI Vision works, but want to see how others are actually using it to reduce risk and improve outcomes at scale. Across construction, manufacturing, and infrastructure, leading organisations have moved beyond pilots and basic compliance to use vision as a core decision-making tool.

Identifying risky behavior is not enough; firms must institute operation-wide behavioral changes to truly uphold safety standards and precautions.

In this session, we’ll show what your peers and competitors are doing differently. You’ll see how teams are identifying risk before incidents occur, redesigning work to be safer by default, and using visual data over time to guide planning, supervision, and intervention, not just report violations after the fact.

If you’re responsible for safety performance, operational risk, or digital transformation, this webinar will give you clear, practical insight into where value is being created today, what “good” looks like in real deployments, and how organisations are turning AI Vision into decisions that stick.

AI Vision is moving from experimentation to enterprise-scale impact. Leading organizations are no longer asking if they should deploy AI Vision, but how to do it in a way that delivers real decisions, measurable value, and long-term scalability.

In this session, we share real-world insights drawn from organizations that have already deployed AI Vision across sites, regions, and functions. From blue-chip enterprises to industry leaders and fast-moving challengers, these teams have navigated the technical, organizational, and operational realities of making AI Vision work in production.

Success doesn’t come from models alone. It depends on a pragmatic path: identifying high-impact use cases, designing the right architecture, aligning Ops, IT, and the business, and building solutions that scale securely and responsibly. Just as importantly, it requires avoiding the common pitfalls that slow teams down or stall pilots before they deliver value.

In this practical session, we share key elements of our enterprise AI Vision playbook, benchmarks from real-world deployments across various industries, and guidance from practitioners who have successfully implemented these solutions. The goal: help you move faster, make better decisions, and avoid lessons others have already learned the hard way.

AI Vision is changing how safety gets done. Instead of after-the-fact reports and clipboard checks, HSE teams are detecting risks in real time. From PPE misses, unsafe proximity, zone breaches, and more, AI Vision is closing the loop on actions and audit trails. With the right architecture, most organizations can leverage existing CCTV to reduce incidents, speed response, and shrink manual audits.

But success depends on a pragmatic path: choosing high-value use cases, aligning HSE/Ops/IT, building worker trust, and designing for compliance (GDPR/ICO, the EU AI Act). And this success is also built on the bedrock of high levels of privacy (a privacy-by-design approach is essential).

In this practical session, we share elements of our playbook, benchmarks from deployments across multiple industries, tools and tips, and best practices. Plus a look at predictive safety and the implications of Visual General Intelligence (VGI) on HSE.

Horizontal Drilling International (HDI) joined us to explore how AI vision is transforming safety operations in complex, high-risk environments. HDI, a branch of VINCI Construction, is a leader in trenchless crossings, landfalls, and horizontal directional drilling for a global portfolio of oil & gas clients.

We go beyond theoretical AI applications and see how computer vision is being deployed at scale, delivering real-time insights, reducing risk, and shaping proactive safety cultures on live construction sites.

Explore the next evolution of AI vision with the viso.ai co-founders.

Go beyond narrow detection models and discover how Visual General Intelligence (VGI) represents a shift toward systems that understand context, infer intent, and deliver foresight: closing safety, compliance, and operational gaps that traditional AI vision can’t.

Explore how AI-powered computer vision is reshaping workplace safety across industries. In this concise, expert-led session, you’ll gain a clear understanding of the shift from manual and reactive safety methods to intelligent, real-time monitoring. Discover how AI vision enhances compliance, reduces risk, and delivers measurable ROI.

In today’s fast-paced and high-risk supply chain environments, safety, efficiency, and real-time visibility are more critical than ever. Computer vision is transforming how organizations monitor operations, detect risks, and optimize processes, without adding complexity.

We explore four high-impact computer vision implementations transforming supply chains today. From preventing forklift accidents to identifying product defect detection and monitoring restricted areas, you’ll gain valuable insights into practical applications that drive measurable ROI.