Everseen CEO Joe White’s Exclusive Interview with MarTech Pulse on Conversational AI

Everact debuts at NRF 2026. For retailers processing 6PB video daily, what’s the wake-up call on conversational AI over reactive loss prevention?

The wake-up call for retail isn’t the addition of a conversational layer, but rather the transition from reactive alerts to contextual intelligence—and that is exactly what Everact delivers.

Everact allows retailers to ask why an incident occurred and whether it reflects a wider, systemic issue.  For example, is a spike in alerts linked to a misprinted barcode, a specific product suddenly becoming a theft target, or a layout problem in a particular aisle? By connecting those dots, retailers can surface patterns that would otherwise remain hidden in raw video data.

That context is then translated into action. When certain thresholds are exceeded, for example, too many alerts in one area or repeated incidents occur with the same self-checkout, Everact presents store and regional managers with clear, prioritized recommendations. It’s essentially a “pre-coffee” action list: here’s what’s happening, here’s why, and here’s what you should fix today to prevent it happening tomorrow.

The conversational AI interface plays a critical role in this. It democratizes access to advanced analytics. Managers don’t need to be data specialists or interpret complex dashboards, they can simply ask questions and get domain-informed answers. That shifts loss prevention from being dashboard-driven and retrospective to being insight-driven and operationally effective.

In short, the wake-up call is this: at petabyte scale, value doesn’t come from more alerts. It comes from context, accountability, and speed – getting the right insight to the right person quickly enough to change outcomes.

Store managers, loss-prevention teams, and C-suite executives all need answers fast. How should Everact’s conversational layer flip how different roles actually work with data, day-to-day?

Everact’s conversational layer is designed to adapt to how decisions are actually made at different levels of the organization, rather than forcing everyone into the same dashboard view.

At the store level, it operates on alert-by-exception. Store managers don’t have time to analyze data, they need priorities. Each morning, Everact delivers a focused “before-coffee” action list: the ten things that matter most today, based on what crossed critical thresholds overnight. Instead of sifting through reports, managers see exactly where intervention is needed and what to do next.

For regional and loss-prevention leaders, the system shifts from simple alerts to guided investigation. They’re notified when patterns emerge across multiple stores, but instead of being locked into fixed templates, they can interrogate the data conversationally. They can ask why a specific store is underperforming, drill into repeat incidents, compare locations, and explore root causes in real time.

At headquarters and C-suite level, the conversational layer becomes a strategic analysis tool. Executives can frame business questions in operational terms and get evidence-based answers without commissioning bespoke reports. For example: “Since introducing self-checkout, why has our loyalty conversion rate dropped?”

Read More: Sales Focus Inc. Founder and CEO Tony Horwath’s Exclusive Interview with MarTech Pulse on Sales Transformation

What’s your dead-simple playbook for early adopter retailers to pilot Everact and measure ROI within 90 days and which 2-3 metrics matter most in that first window?

Every business has different priorities, risk profiles, and operating models, so ROI is defined differently for every organization. That being said, there is one metric that consistently emerges as transformational: time to resolution.

Everact is uniquely positioned to compress the entire problem–solution cycle—detecting an issue, understanding its root cause, and fixing it on the shop floor. Instead of waiting weeks or months for resolution, Everact turns it  into days or even hours. That compression is the real game changer.

Traditionally, retailers might identify a problem weeks after losses have accumulated, commission analysis, distribute reports, and only then attempt remediation. By that point, the damage is already done. Everact reverses that model.

Whether it’s an unreadable barcode, systematic product switching, or process breakdowns at self-checkout, the time between problem and fix is dramatically shortened.

Vision AI and agentic AI are battling buzzwords. What are retailers’ top 2 misconceptions about Everact, and what should they actually expect under the hood?

At this stage, the biggest challenge isn’t misconception, it’s familiarity. Everact is still new enough that most retailers don’t yet have fixed assumptions about it. The market is crowded with “Vision AI” and “agentic AI” claims, so the dominant issue is noise, not misunderstanding.

That said, when retailers first encounter Everact, two expectations tend to surface, shaped by that broader hype cycle.

The first is that Everact is “just another AI layer” sitting on top of video. Some assume it’s primarily about automation, chatbots, or surface-level visual recognition. In reality, under the hood, Everact is a domain-specific intelligence system that fuses video, transaction data, and operational context. Its core value is not recognition, but explanation – understanding why events happen and what they mean for the business.

The second is the idea that “agentic AI” means full autonomy. There’s a perception that the system will magically make decisions and run stores on its own. That’s not how Everact is designed. It doesn’t replace human judgment; it amplifies it. The platform surfaces evidence, patterns, and recommendations, and routes them to the right people, but accountability remains with operators and managers.

What retailers should actually expect under the hood is a purpose-built analytics engine trained on real retail loss and operations data, embedded with domain expertise. It continuously correlates video behavior, transaction anomalies, and historical patterns to generate contextual insights.

Your co-innovation program launches in Q2 2026. What 2 underrated competitive advantages do forward-thinking retailers unlock by being early collaborators with Everseen’s product and AI research teams?

Early collaborators will unlock two underrated competitive advantages.

First, they dramatically shorten the time between problem and fix. By helping shape how Everact detects and explains issues, they learn to move from first signal to remediation in hours or days, while competitors are still reviewing reports. Faster fixes mean faster revenue recovery and sustained bottom-line impact.

Second, they embed their own operational reality into the platform. Working directly with Everseen’s product and AI teams ensures Everact is tuned to their formats, workflows, and risk patterns from day one. That creates intelligence that fits their business, not a generic model competitors can easily copy.

Put simply, they see issues earlier and deal with them before competitors even know there’s a problem.

Read More: Horizon Media EVP & Head of Platform Partnerships John Koenigsberg’s Exclusive Interview with MarTech Pulse on Predictive AI

Which 3 operational KPIs should retail leaders obsess over daily in an Everact- enabled world and which 2 legacy metrics can they finally stop tracking?

With Everact, the priority isn’t to abandon traditional metrics, but to focus on the ones that drive faster action. There’s no real need to stop tracking anything because legacy KPIs still matter. What changes is what leaders focus on every day.

Three operational KPIs stand out.

First is time to resolution: how quickly teams move from detecting a problem to fixing it. This is the clearest signal that insight is turning into impact.

Second is friction impact: how much operational or customer friction is being created by loss-prevention activity, including false positives and unnecessary interventions.

Third is value recovery: how much preventable loss is being avoided or recovered through targeted, explainable actions.

As for legacy metrics like stop rates and recovery ratios, they don’t need to disappear. They just stop being the headline. Instead of managing by raw counts, leaders manage by understanding what’s driving loss, how fast it’s being fixed, and what that means for the business in real time.

Joe, as we wrap up what’s the one step retail technology leaders reading MarTech Pulse should take today to position themselves ahead of Everact’s Q2 2026 pilot program before spots fill up?

So the simplest step is to reach out early and get on the roadmap before spots fill up. Retailers who get the most value from Everact will be the ones who engage early—before pilots are fully allocated and before priorities are locked in.

Thank you, Joe White,  for taking the time to share your insights with us.

Write to us [⁠wasim.a@demandmediaagency.com] to learn more about our exclusive editorial packages and programmes.