Every engagement below started with a business problem, not a technology preference. Client names are withheld under NDA; the constraints, decisions and measured outcomes are exactly as they happened.
Each of these is a real build. We have kept the numbers the client measured, not the ones that flatter us — and linked the service page that covers how we approach that kind of work.
18,000 monthly deliveries coordinated on spreadsheets and messaging apps. We built one shared delivery record — offline-capable driver capture, proof of delivery, customer tracking and billing readiness in a single system.
A multi-site clinic group was running intake on paper and three disconnected systems. We replaced it with a single HIPAA-aligned platform: digital forms, insurance verification and EHR sync in one flow.
Analysts spent most of their day extracting figures from PDFs. We built a document pipeline with LLM extraction, confidence scoring and a human review queue, wired into their existing decisioning system.
Growth had outrun the original architecture — every new customer meant a new deployment. We moved them to a pooled multi-tenant model with per-tenant isolation, self-serve onboarding and usage-based billing.
Dispatchers were reconciling shipments by hand across carrier portals. We built an integration layer with queued sync, idempotent writes and a live exception board so problems surface before the customer calls.
The storefront buckled under campaign spikes and the cloud bill grew regardless. We re-architected caching, moved to autoscaling containers and rebuilt the checkout path around measured bottlenecks.
A founder with deep domain knowledge and no engineering team. We scoped hard, built the smallest defensible first release, and put it in front of three pilot plants before adding a single extra feature.
Different industries, same discipline: understand the constraint before choosing the technology, ship something real early, and measure whether it moved the number that mattered.
We start with the number that is hurting — intake time, reconciliation hours, cloud spend, churn — and trace it back to where the system actually breaks. Often the answer is smaller than the brief we were handed.
Every feature in the first release has to earn its place by answering a question. Everything else moves to a second list that we revisit once real usage tells us which items still matter.
The same people who scoped the work write the code. You see running software every two weeks in an environment that mirrors production, so integration problems appear early rather than at handover.
Thirty to ninety days after launch we go back to the metric we started with. If it moved, we plan the next increment against it. If it did not, we say so and work out why before spending more of your budget.
Bring it to a free discovery call. We will tell you what we would build, roughly what it costs, and honestly whether it is worth doing.