A redesign of Solink's Events search — introducing a flexible query builder and saved searches so teams could explore video + PoS data more effectively with less reliance on support.

Users struggled to quickly find relevant moments and patterns across large volumes of video and operational data, slowing investigation and response.
Solink pairs Point of Sale data with real-time video to create a cloud-based dashboard of searchable moments. Users can quickly review movement in a room, verify purchases, or identify unusual behavior. This approach has reshaped the surveillance space and positioned Solink as a central platform for operations, security, and loss prevention across restaurant, retail, and financial sectors.
Each customer in the Solink ecosystem captures different types of video and PoS data. These variations create a significant challenge when searching and reporting at scale. For example, one customer may want to track staff discount abuse, another may want to measure the success of a product promotion, and another may want to count secure-room access events using motion data.
Customer feedback made it clear that the search tools were too simple and rigid. Users could only filter predefined reports with one or two search terms, which limited their ability to find meaningful events. They wanted more freedom to explore their data and uncover insights.


Finding the right moment in Solink wasn't a simple search problem. Users were working under time pressure, sifting through large volumes of video and event data where relevance was often unclear upfront. Small mistakes in filtering or interpretation could mean missing critical signals, so the experience had to balance speed with confidence, helping users narrow in on what mattered without overwhelming them with noise.
Increase how often users interact with and rely on the events page.
Give users the flexibility to find the specific events and patterns they care about.
The final design appeared straightforward, but the system required significant engineering effort. We worked through the complexity over multiple sprints and met regularly with engineering to plan, review, and ensure the design was implemented as intended.
We prioritized clarity and speed over exposing every possible filter upfront.
Users can now build complex searches by combining multiple search terms with AND/OR logic.
Custom searches can be saved as reports and shared across teams, reducing dependency on support.
Customer success reported positive experiences as they used the Events page in their daily work, and sales shared encouraging feedback from customers who found the improved search much easier to use.
Users spent more time exploring events and using the enhanced search tools.
Users created more custom reports from their searches, reducing reliance on support.
Users added custom search results to their automated weekly digests more frequently.
These teams had far more day-to-day contact with customers than product did, and their insights were essential to shaping and landing the feature. Their feedback helped us refine the experience and ensure it resonated with users.
Implementing a complex feature in a single push is rarely effective. Breaking the work into multiple sprints helped derisk the effort, gave engineering room to solve technical challenges, and allowed us to deliver value steadily while working toward the full vision.