Backend systems, mobile apps, and the data infrastructure powering Hoomanely's software stack.
Every social app eventually hits what we call the Feed Scaling Wall. It usually shows up the moment your first power user follows their 500th account, and the once-snappy SELECT * query that powered their feed starts taking 200ms. Then 500ms. Then it times out. To get ahead of this at
Hoomanely products aren't just mobile apps or hardware devices in isolation anymore. They're systems, a combination of sensors, firmware, mobile apps, dashboards, and cloud intelligence. As we build connected pet devices and real-time insights, one question keeps coming up: can we stream live device data directly
Modern backend systems rarely fail loudly. They fail quietly, through duplicated requests, partially completed workflows, retried executions, and replayed messages that look successful but slowly erode correctness. On AWS, these behaviors aren't edge cases or misconfigurations, they're the default operating conditions of a resilient, distributed platform.
At Hoomanely, we're building a preventive pet healthcare platform for pet parents that has tools and features ranging from a pet-parents community to an AI-powered pet care chat assistant. Our mission demands rapid iteration, we need to test hypotheses quickly, deploy features fast, and scale efficiently without the
Modern apps are full of notifications, reminders, and generic tips, and most of them get ignored. At Hoomanely, we wanted something very different: a feature that feels personal, timely, and useful without overwhelming the user. That idea became Paw Pulse, a daily, context-aware insight designed specifically for each pet. This
At Hoomanely, our app lets users upload pet photos during onboarding, attach images to community posts, share short video clips, upload pet tag images, submit food label photos for AI analysis, and update profile and cover photos. Each of these flows generates large media files, often multiple megabytes per upload,
Ask any pet parent about their anxious dog, and they'll give you a novel. Ask an AI assistant the same question without proper context, and you'll get generic advice that could apply to any animal, anywhere. Here's what we learned building Hoomanely's
Imagine this: you're chatting with an AI vet about your anxious rescue dog, Luna. Over hours, you've discussed her separation anxiety, dietary restrictions, medication schedules, and behavioural patterns. Then the next day, you ask a follow-up question about her progress, and the AI responds as if
When you're building a pet health app, speed matters. A dog's nutritional needs shift with age, breed, activity level, and health conditions, and waiting 2-4 days for app store review just to push a content update is too slow when pet parents need real-time guidance. That&
Onboarding friction kills conversion. When building Hoomanely's pet parent onboarding flow, we discovered that one seemingly simple question, what breed is your pet, can cause unexpected dropoff. Pet parents would pause, scroll through endless dropdown menus, type partial breed names that didn't match our taxonomy, or