Real Work, Real Outcomes

Clinicians and practices were spending many hours manually reviewing patient data and assembling reports tailored to each practice’s specific needs.

We built a generative-AI product that analyzes patient data and produces reports matched to each practice’s requirements, designed around how clinicians actually work.

The product saves clinicians and practices many hours of manual effort, returning their time to patient care instead of data wrangling.

An early-stage healthcare startup needed to turn a nascent team into a dependable engineering organization capable of delivering and scaling.

We provided hands-on technical leadership, establishing engineering practices, guiding hiring and team structure, and mentoring the team toward autonomy.

The startup grew into a well-functioning engineering team with the leadership foundation and practices to keep scaling.

The firm ran on large single-instance Windows infrastructure that could not scale to handle growing load or support distributed processing.

We re-platformed onto Azure Container Apps and Container App Jobs for elastic, distributed workloads, and added observability across the stack to give the team clear visibility into production.

The platform now scales to support higher load and distributed systems, and the team has the observability to deliver and monitor production reliably.

The retail company’s Marketing Ops team needed richer insight, but their data sat scattered across disconnected systems like their CRM and marketing channels.

We built integrations across their technology stack and constructed a full data warehouse with bronze, silver, and gold layers, turning raw source data into clean, analytics-ready insight.

Marketing Ops gained unified, richer insight across their stack, sharpening their ability to understand performance and act on it.