MIXT leverages Spot AI for operational excellence in 20 restaurants

Challenge 1: Unreliable retention, bandwidth constraints, and access difficulties

MIXT tried various security systems before Spot AI, all of which presented their unique challenges. Recording failures were frequent, access to NVRs complicated, and permission issues common with different passwords and access methods across sites. Before Spot AI, IT were the only system users because of complex processes to manage users, logins, and footage.

“We tried various systems before Spot but faced frequent recording failures, complicated NVR access, and permission problems. We tried a fully cloud-based system, but it had bandwidth limitations, making real-time viewing impossible. Spot's hybrid approach solved all our problems. It just works.”
David Silverglide, Co-Founder and President

Solution 1: Hybrid cloud model: A system that “just works”

Spot AI's hybrid approach, which combines on-site and cloud-based recording with simplified management, provided the perfect solution to MIXT’s problems. They now have dependable footage retention, easy access to live viewing, and simple system management.

They’ve gone from just a few users to over 40 in all departments: GMs, operations, finance, and executive teams all use Spot AI to gain the on-the-ground context they need. Finance uses the system to verify the reasons behind particularly high or low revenue periods, operations uses it to monitor restaurants in real time using remote video walls, and executives are able to effectively resolve incidents using video context and Cases.

“Our Finance team members are big users now. Instead of needing to ask a GM things like ‘Why was there no revenue from 2 to 5 yesterday?’ in the case of a fire alarm, they can pull the camera footage up in seconds to see what happened.”
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David Silverglide, Co-Founder and President

Challenge 2: Time-consuming incident resolution

Resolving incidents such as chargebacks, break-ins, and time theft was a time-consuming process for MIXT. Every incident required extensive manual review and investigation. This led to large amounts of wasted time, incomplete investigations, and unnecessary payouts for incidents like chargebacks, where recipients of delivery and catering orders claimed that they didn’t receive certain orders.

Solution 2: Built-in Cases to mitigate risk of chargebacks, break-ins, time theft, and other incidents

With Spot AI, MIXT can now instantly investigate and resolve all incidents that occur in their restaurants using powerful AI search features and Cases. Cases is a built-in case management feature that allows users at MIXT to save clips to the cloud forever, add documents, and collaborate with internal and external parties to resolve investigations effectively. 

Spot AI helped MIXT:

• Identify dozens of fraudulent chargebacks on delivery orders, saving thousands of dollars
• Mitigate risk associated break-ins in downtown San Francisco
• Uncover incidents of time theft and employee-manager collusion
• Improve insurance claim effectiveness in the case of a flooded restaurant

“Delivery and catering customers sometimes claim they didn’t get their food when they actually do, but the delivery providers automatically process those chargebacks. With Spot AI, we can instantly go back to them with a screenshot or clip and get the credit back for it.”
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David Silverglide, Co-Founder and President

Challenge 3: Variable staffing needs

MIXT found it challenging to determine the optimal staffing levels at their restaurants, which vary by location and time of day. This has a direct impact on business efficiency and customers' experiences.

Solution 3: Optimized staffing using queue data powered by AI

MIXT has idle time dashboards configured at every location to analyze queue data and optimize staffing levels across all locations. MIXT can see the average line lengths at every location, and allocate more staff to locations that typically have longer lines, while cutting back in the stores that have shorter lines. Previously, they used more anecdotal evidence for queue lengths, but having this visual context has improved both efficiency and customer experience across their restaurants.

“We use AI to figure out line flow and queue length versus number of employees serving those guests. Having queue data normalized over longer periods helps us figure out where we need more bodies.”
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David Silverglide, Co-Founder and President

Conclusion

Spot AI has resolved MIXT's IT challenges like unreliable retention and bandwidth constraints, while empowering 40+ users to use video context to mitigate risk, improve staffing, and enhance customer experiences. As MIXT continues to grow, Spot AI will remain an integral part of its strategy, helping serve excellence at every restaurant. Discover more about how Spot AI can solve your biggest challenges by watching our webinar.