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Spicy Bytes: Physical Security Edition, Featuring Milestone Systems

August 6, 2026
Meg McHughAlliance Marketing Manager, Surveillance

Spicy Bytes is a Wasabi TV exclusive that puts business leaders through a unique challenge: hot wings paired with real conversations about technology, partnerships, and the trends shaping their industries. In this episode, I sat down with Mark Vella, Wasabi's VP of Global Business Development, and Tim Palmquist, VP of U.S. & Canada at Milestone Systems, for a discussion that started with physical security and quickly expanded into data strategy, cloud economics, and responsible AI.

One idea connected every part of the discussion. For years, organizations deleted enormous amounts of video they would now consider valuable. Storage costs made long-term retention difficult to justify, limiting how much organizations could preserve and learn from over time. Tim opened the conversation by explaining why that way of thinking no longer fits the industry he's seeing today.

A history of lost opportunity

Traditionally, the physical security industry has been defined by what Tim called "guns, guards, and gates." He now sees it through a broader lens: safety, security, and liability management. Increasingly, businesses are adding a fourth priority as well: operational intelligence and predictive insight.

That last category changes the role video plays inside an organization. Instead of serving only as evidence after something happens, it becomes a source of information that can reveal patterns, improve operations, and help organizations make better decisions over time. As Tim put it, "data is the new oil."

For decades, though, there was a practical problem. Organizations routinely deleted surveillance footage after 30 to 90 days because storing months or years of video simply cost too much. The footage still had potential value; it’s just that few could justify paying exorbitant storage costs to keep it.

What that deletion cycle actually cost organizations is easy to underestimate. Operational patterns that only surface over months, like staffing gaps, traffic flow issues, and recurring safety incidents, require a long enough record to even become visible. Compliance requirements that call for historical evidence had nothing to point to once the footage window closed. And the analytics tools now capable of finding those patterns arrived after most of the data they needed had already been erased.

Storage economics finally catch up

Mark drew a parallel to another technology transition that many IT teams have already experienced.

As enterprise IT embraced the cloud, the S3 API emerged as the standard for object storage, giving organizations the flexibility to move data across platforms. At the same time, data itself became more valuable. Businesses began retaining information for longer because they saw new opportunities to analyze it, apply AI, and extract more value over time.

Mark believes video is following the same trajectory. Organizations are storing more footage because historical footage has become useful for analytics, AI, and compliance. The longer that information survives, the more opportunities organizations have to extract insight from it.

Tim approached the same shift from the customer's perspective. Organizations may want to retain more video data, but they also need confidence that they can access it when needed. That's one of the reasons Milestone welcomed Wasabi as a partner. Alongside its focus on the physical security industry and its partnership-first approach, Wasabi's predictable pricing model removes a major obstacle by eliminating egress fees. Customers don't have to second-guess what it will cost to retrieve archived footage months or years later.

Keeping the data is only the beginning

As organizations keep more historical video footage, the conversation naturally shifts from storage to stewardship. How data is collected, governed, and ultimately used becomes just as important as how long it remains available.

That was a recurring theme throughout the discussion. Both Mark and Tim emphasized that responsible AI isn't emerging as a response to public concern. It's being treated as a foundation for how the industry moves forward.

Tim pointed to Milestone's Project Hafnia as one example. The initiative focuses on responsibly sourced data lakes for AI training, recognizing that stronger AI depends on more than larger datasets. The quality of the data, how it was collected, and the standards surrounding its use all shape the outcome.

That distinction matters more in physical security than in most other industries working with AI. Video is uniquely personal data, and an industry already associated with the word "surveillance" doesn't have the benefit of assuming good faith from the public. For Milestone, sourcing that data responsibly is what allows customers and regulators to trust the output at all.

That same philosophy extends beyond a single project. As organizations retain more video and generate more opportunities for AI-driven insight, trust becomes part of the technology itself. Privacy, transparency, and responsible data practices determine whether customers are willing to embrace the next generation of AI applications.

Pillars of a successful partnership

Tim closed the episode by outlining four priorities he believes will define successful technology partnerships in the years ahead: AI transformation, rapid innovation, edge-to-cloud architecture, and trust and responsibility.

Taken together, they describe an industry entering its next phase. Affordable cloud storage made long-term video retention practical. AI gives organizations new ways to learn from that history. The companies that stand out will be the ones that treat responsibility as part of the technology, not an obligation that begins after it's built.

Spicy Bytes with Milestone Systems

Watch the Full Episode

Security incidents are the obvious use case, but the bigger opportunity is operational: staffing patterns, traffic flow, recurring issues at specific locations or times. Those patterns only become visible with enough historical data to compare against, which is exactly what got lost when footage was routinely deleted after 30 to 90 days.

It refers to how the footage used to train AI models was collected and whether the people and organizations that generated it consented to or were informed about that use. It's a higher bar than simply having a large volume of video, which is the distinction Project Hafnia is built around.

Not necessarily. Most organizations in this space are managing a mix of on-prem and cloud infrastructure rather than switching wholesale, and the economics discussed in this episode are specifically about what changes when long-term retention moves to the cloud, not a case for eliminating on-prem systems altogether.

Teams that would normally ration how often they pull archived footage, to avoid retrieval charges, can instead treat the archive as something to query freely. That shifts video from an occasional forensic resource to something analytics and AI tools can draw on routinely.

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