Healthcare & Pharma
In healthcare and pharma, software isn't just an operational tool. It's a compliance surface. We build and modernize systems with that reality baked in from the start, not retrofitted at the end.
The software challenges in healthcare and pharma aren't generic. A system migration is a validation exercise. A new data pipeline is a potential audit finding waiting to happen. Most technology consultants learn this the hard way, on your timeline and your budget.
We already know it. GxP validation, 21 CFR Part 11, data integrity requirements, electronic batch records, clinical trial data handling. We've worked in these environments. That domain depth means we start solving on day one, not after a three-month discovery phase where we're reading your SOPs for the first time.
We bring AI-assisted engineering into every engagement. Not as a buzzword, but as a way to compress timelines, reduce rework, and improve documentation quality. And we do it in a way that respects your validation requirements, not one that creates new ones.
We modernize core systems (EHRs, LIMS, MES, document management) with a validation-first approach. No shortcuts that create downstream audit exposure. Phased, documented, and built to survive an FDA inspection.
We've done the work of understanding where AI-assisted development fits within a validation framework, and where it doesn't. Faster delivery without creating new compliance risk is a real thing. We'll show you how.
A validated platform, built once and deployed across multiple sites, business units, or even clients, instead of revalidating from scratch every time. Custom SaaS makes that possible. Especially powerful in regulated industries where validation cost is a real burden.
Domain knowledge you shouldn't have to pay to teach us
"We know what a validation looks like. We know what an audit finding costs. We build accordingly."
Related
March 2026
How domain knowledge, engineering experience, and Anthropic's Claude Code compressed a regulated software deployment from the typical twelve months to under three. Delivered as Custom SaaS, not a project.
November 2025
How we built inventory visibility for a pharma manufacturer in 10 weeks — without replacing their GMP paper records. Layer, don't replace.
January 2026
How we architect secure Azure environments where sensitive health data stays protected while enabling AI/ML research at scale. Architecture beats policy.