DataViz Inc sold business intelligence, but their own product showed yesterday's numbers. Reports ran as overnight batch jobs, so by the time a customer acted on a trend it had often already turned. They needed the dashboard to reflect the business as it happened, without melting the database every time someone opened a chart. We separated the write path from the read path. Events stream into an append-only store and are continuously rolled up into pre-aggregated views, so a dashboard query reads a small, ready-made summary instead of scanning raw events live. A streaming layer pushes updates to the browser over websockets, so the numbers move on screen without anyone hitting refresh. Charts that used to lag a full day now update within seconds of the underlying event, and they do it under real load because the expensive aggregation happens once on write, not on every view. DataViz turned "real-time" from a roadmap promise into the feature their sales team leads with.
ShopEasy had outgrown the monolith that built their business. Every sale season was a gamble on whether the single application server would survive the traffic, and a change to the checkout meant redeploying the entire store. The platform was not broken; it was simply unable to grow at the pace the business now needed. We migrated incrementally rather than rewriting from scratch - the strangler approach, peeling off one capability at a time behind a stable API so the live store never stopped selling. Catalog, cart, and checkout each became services that scale on their own, containerized and orchestrated so capacity follows demand instead of being provisioned for the worst case all year round. The result was a platform that absorbs seasonal spikes by scaling the services that actually feel them, while the rest stay lean. Deploys went from a coordinated event to a routine, several-times-a-day non-event, and the infrastructure bill dropped because ShopEasy stopped paying year-round for peak-day capacity.
Global Bank Corp came to us with a banking platform that worked and that nobody enjoyed using. Customers completed tasks despite the interface, not because of it, and the support queue told the story - the same handful of screens generated most of the calls. We started with the calls, not the comps. Three weeks of session reviews and support-ticket analysis showed the real friction was not visual; it was a transfer flow that asked for the same information twice and a dashboard that buried the one number people opened the app to see. We rebuilt the information architecture around what customers actually did most, redesigned the core flows to remove the duplicate steps, and shipped a design system the bank's own team could extend. The redesign cut the steps in the primary transfer flow by nearly half and moved the most-requested information to the first screen. Within a quarter, the support volume tied to those screens fell sharply, and the bank's team was shipping new features on the system without coming back to us for every change - which is the outcome we are proudest of.
