Health Tech

SOFTWARE ENGINEERING FOR US HEALTH TECH

The rigor of healthtech, at AI’s pace.

We embed engineers trained in the craft that keeps AI-accelerated engineering safe, compliant, and built to last.

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AI is only as good as the team using it.

AI compounds whatever a team already brings. We spent years building the discipline it now amplifies.

Spec before code.

The thinking happens before a line is written, so the build stays on target and rework stays small.

Test-first, always.

A failing test sets the target. Code earns its way in by passing it, not by looking right.

Clean code, by habit.

We refactor as we go, so the codebase stays fast to work in long after we hand it over.

AI in production. Here's what it took.

AI products we shipped for US health tech, built with AI and the judgment to know when it’s wrong.

Ideation to live
MVP in three months.

A retrieval platform with no-code agentic workflows, wired to 20+ language models. Now live at Virginia Tech and Providence College, with manual academic work cut in half.

Read the Rolai story

Ideation to live
MVP in three months.

A retrieval platform with no-code agentic workflows, wired to 20+ language models. Now live at Virginia Tech and Providence College, with manual academic work cut in half.

Read the Rolai story

Ideation to live
MVP in three months.

A retrieval platform with no-code agentic workflows, wired to 20+ language models. Now live at Virginia Tech and Providence College, with manual academic work cut in half.

Read the Rolai story

AI work that compounds across your engineering organisation.

Adoption, codebase, or feature work. The engineering craft underneath is the same.

AI Enablement

The infrastructure that makes AI adoption safe, measurable, and consistent across your engineering organisation. Productivity that holds past the first quarter.

AI Enablement

The infrastructure that makes AI adoption safe, measurable, and consistent across your engineering organisation. Productivity that holds past the first quarter.

AI Enablement

The infrastructure that makes AI adoption safe, measurable, and consistent across your engineering organisation. Productivity that holds past the first quarter.

Built for the realities of US health tech.

Three health tech verticals where regulation is the design starting point

PAYER TECH

Claims, eligibility, member AI.

Compliance review, claims processing, and member-facing AI, defensible across CMS and Medicare audit cycles.

PAYER TECH

Claims, eligibility, member AI.

Compliance review, claims processing, and member-facing AI, defensible across CMS and Medicare audit cycles.

PAYER TECH

Claims, eligibility, member AI.

Compliance review, claims processing, and member-facing AI, defensible across CMS and Medicare audit cycles.

Our engineers ship faster because our Claude plugin codifies our craft.

Bee is the Claude Code plugin we built for ourselves and open sourced. It knows our practices, enforces our standards from discovery through review, and ships with every engineer on every client engagement. It's also the template for what we build for your team. When we set up your AI infrastructure, we draw from what we've already lived.

Your foundational model may be replaceable. Your forward-deployed engineers aren’t.

Foundation models are commoditizing. Defensibility shifts to forward-deployed engineers embedded inside your team. That bench is the moat.

OPTION 01 · ACQUIRE

$4 billion

OpenAI’s reported price for Tomoro’s 150 forward-deployed engineers. Out of reach for the rest of the AI platform market.

OPTION 02 · BUILD

18 months

Hire, vet, train, deploy, and maybe ship in eighteen months. By then your customers have moved to a platform that already has the bench.

OPTION 03 · FOUNDRY

Build. Operate. Transfer.

We build a captive of eight to twelve FDE-grade engineers, branded as yours, trained on your platform, embedded with your team, and transferred to you in 24 to 36 months.