Migrate from Verkada to Spot AI

Migrate from Verkada to Spot AI: a step-by-step guide for 2026

You can migrate from Verkada to Spot AI on the cameras you already own. Verkada's Command Connector supports third-party ONVIF and RTSP, and Spot AI is camera-agnostic, so the physical cameras on your walls stay in place while the intelligence running on top of them changes. This guide walks a security or IT leader through the whole move in four phases, with a parallel run so no site ever loses coverage or an evidence trail.

The timing lines up with where most teams already are. In 2026, 47% of security leaders rate cloud migration and security as a "very important" focus area (Source: Security Magazine), and operations teams still spend nearly three hours a day manually triaging alerts (Source: Security Magazine). A migration is your chance to fix both without a rip-and-replace.

Here is the whole migration at a glance. Each phase is broken out in detail below, and the table is the plan you can share with IT and procurement in one screen.

What carries over when you migrate

The biggest fear in any platform move is that switching means ripping cameras off the wall. It does not. Verkada is a cloud platform that sells its own cameras, but its Command Connector supports third-party ONVIF and RTSP cameras, so your estate is already speaking open standards. Spot AI is software-led and camera-agnostic, working with any IP camera you already own. That combination is what makes this a low-risk migration rather than a capital project.

Here is what stays and what changes:

• Your cameras stay. Existing IP cameras connect to Spot AI over ONVIF or RTSP. Legacy analog cameras can be brought in through the IVR, so older zones are not stranded.
• Your cabling and mounts stay. No trenching, no re-pulling cable, no new mounting hardware to move cameras that already have the angles you want.
• Your coverage stays. Because you run both platforms in parallel during cut-over, every camera keeps recording throughout the move.
• The intelligence changes. Instead of on-camera analytics tied to specific hardware, Spot AI applies 15+ pre-trained Video AI Agents plus Iris custom detections and contextual active deterrence on any camera with standard speakers.

This is not theory. A major North American building-materials maker with roughly 1,000 sites had deployed Verkada cameras for AI safety monitoring; the cameras worked but the analytics fell short. Rather than replace anything, the team ran Spot AI on the existing Verkada cameras via RTSP plus Starlink, with zero cameras replaced, and is scaling toward 100 sites. If you want the business case behind that decision, the why switch from Verkada to Spot AI breakdown and the current Spot AI vs Verkada comparison cover the tradeoffs in detail.

It is worth being precise about the honest contrast here, because it is architecture and cost, not a claim that one platform lacks a capability. Both platforms offer real-time active deterrence. The difference is what each one requires to deliver it. Verkada's full AI and its AI-Powered Deterrence run on its own gen-2 or newer cameras plus dedicated audio hardware such as a horn speaker or intercom, so extending deterrence usually means buying more Verkada hardware. Spot AI's contextual AI Talk Down runs on any camera you already have with standard speakers. On a large multi-site fleet, that is the line item that decides whether modernizing your video is a subscription change or another hardware purchase.

The migration in four phases

Treat the move as a project with clear gates, not a flip of a switch. Each phase below lists what to do, how to do it, and the pitfall to avoid.

Phase 1: Assess your current Verkada estate

What: Build a single inventory of every camera (make, model, and whether it is reachable over ONVIF or RTSP), the network at each site, your retention requirements, and your Verkada license renewal dates. How: Pull the camera list from Verkada Command, confirm which units already run through the Command Connector as third-party devices, and map open investigations that need footage continuity. Pitfall: do not assume proprietary lock-in and quote yourself into a full hardware refresh. Most estates are more portable than they look, and the renewal calendar is what should drive your sequencing, not fear of the cameras. Use the Verkada pricing breakdown to model what you stop paying at each renewal.

Phase 2: Run a pilot on a subset of cameras

What: Prove the platform on a representative site before you commit the fleet. How: Connect a small, honest cross-section of existing cameras to Spot AI over ONVIF or RTSP, then validate the agents that matter to you on live video: unauthorized entry, loitering, vehicle detection, and AI Talk Down deterrence. Compare detections and alert quality against what Verkada surfaces on the same cameras during the same window. Pitfall: do not cherry-pick your best-lit, best-angled cameras. Pick the messy ones too, because the pilot only de-risks the rollout if it reflects real conditions. The building-materials example above is a working proof that agents can run on cameras that were originally stood up for another platform.

Phase 3: Cut over site by site with a parallel run

What: Move production coverage to Spot AI in waves while Verkada stays live underneath. How: Group sites by renewal date and complexity, stand each one up on Spot AI, verify agents and alert routing for a defined overlap window, then mark the site as cut over. Keep both platforms recording until each site passes its checks. Pitfall: sequencing sites out of order can leave you double-paying Verkada longer than you need to, or cutting a critical site before the team trusts the new alerts. Let renewal dates and site risk set the order. This parallel-run discipline is what removes the coverage gap that makes teams hesitate to switch at all.

Phase 4: Tune agents and expand

What: Turn a working deployment into an operational advantage. How: Configure agents and alert thresholds to your standard operating procedures, enable contextual active deterrence where it fits, and use Iris to build any custom detections your sites need. Once security is stable, many teams expand the same cameras into safety and operations use cases. Pitfall: over-alerting on day one. Start with a short list of high-value detections, prove the signal, then widen. For a fuller view of where each platform lands after tuning, see the Verkada limitations rundown and the broader Verkada alternatives for 2026.

How Spot AI handles data and footage retention during migration

Retention is where migrations quietly go wrong, so handle it deliberately. The parallel run already gives you an overlap window where both platforms are recording. Use it: before you decommission anything on the Verkada side, export and preserve footage tied to any open investigation or legal hold, and confirm your new retention windows on Spot AI match or exceed policy. Nothing should be deleted until the corresponding Spot AI coverage is verified.

Architecturally, the model shifts in your favor. Spot AI's edge-first IVR keeps full-resolution video inside the facility and sends only metadata across the network, which lowers bandwidth load, keeps deployments PCI-clean, and simplifies data-residency questions. The platform is NDAA-compliant and SOC 2, and evidence stays time-stamped and case-ready. If chain-of-custody is part of your requirements, the video retention and chain-of-custody guide and the SOC 2 and data security overview lay out how to document it during and after the move.

Migration checklist

Copy this into your project plan and check it off site by site.

1. Inventory every camera with make, model, and ONVIF or RTSP reachability.
2. Map Verkada license and contract renewal dates to set your cut-over order.
3. Identify open investigations and legal holds that need footage continuity.
4. Connect a representative pilot set and validate agents on live video.
5. Define the parallel-run overlap window and success criteria per site.
6. Cut over in waves, verifying alerts and coverage before retiring each site.
7. Preserve and export any open-case Verkada footage before decommissioning.
8. Confirm Spot AI retention windows meet or exceed policy.
9. Tune agents and active deterrence to your SOPs, starting with high-value detections.
10. Retire redundant Verkada licenses at renewal and reallocate the budget.

"With Spot AI, we're talking about five minutes, tops, to resolve an incident now."

Dale Byrge, Director, Information Technology, Liberty-Perry School District

That kind of resolution speed is the point of the move. Once the AI Security Guard is watching your existing cameras, the same footage that used to sit in an archive becomes an AI coworker that detects in context, deters in seconds, and documents case-ready evidence. When you are ready to scope your own migration on the cameras you already run, book a demo and walk through it site by site with the Spot AI team.

Frequently asked questions

Do I have to replace my cameras to move from Verkada to Spot AI?

No. Verkada's Command Connector supports third-party ONVIF and RTSP cameras, and Spot AI is camera-agnostic, so your existing IP cameras connect over the same open standards. Legacy analog cameras can be brought in through the IVR. A building-materials maker ran Spot AI on its existing Verkada cameras with zero cameras replaced.

Will there be a coverage gap during the migration?

No, if you run the platforms in parallel. During cut-over, Verkada stays live underneath while each site is verified on Spot AI, so every camera keeps recording. A site is only retired from the old platform after it passes its checks on the new one.

What happens to my existing Verkada footage and open investigations?

Preserve it deliberately. Before decommissioning anything, export and hold footage tied to any open investigation or legal hold, and confirm your new retention windows meet policy. The parallel-run overlap window is designed to give you time to do this without losing a chain-of-custody trail.

How long does a Verkada to Spot AI migration take?

A pilot on a subset of cameras can reach live video in days to two weeks. A full fleet cut-over typically runs 2 to 8 weeks depending on the number of sites, sequenced by contract renewal dates and site risk. Tuning continues after go-live.

Is Spot AI more secure than staying on my current platform?

Spot AI is NDAA-compliant and SOC 2, with an edge-first IVR that keeps full-resolution video in the facility and sends only metadata across the network. For context on why security leaders scrutinize cloud video, the FTC required Verkada to build a comprehensive information security program and pay a $2.95 million penalty over 2024 charges tied to a 2021 breach that exposed more than 150,000 live cameras (Source: Federal Trade Commission).

About the author

Joshua Foster is an IT Systems Engineer at Spot AI, where he focuses on designing and securing scalable enterprise networks, managing cloud-integrated infrastructure, and automating system workflows to enhance operational efficiency. He is passionate about cross-functional collaboration and takes pride in delivering robust technical solutions that empower both the Spot AI team and its customers.