Custom software for Madison — built the AI-native way.
We pair senior engineers with an AI-accelerated delivery model to ship custom software for Madison's healthtech, research, and B2B SaaS operators — without the fragile output that gives AI a bad name.
AI changed the economics of custom software. We rebuilt our process around it.
Madison anchors one of the country's deepest healthtech markets — built around Epic Systems and the UW research-software ecosystem — plus a serious insurance, ag-tech, and B2B SaaS scene. Senior hires are six figures, months out, and picked over by Epic, American Family Insurance, and the venture-backed startups around them. AI changes the math, but only when senior people own the parts AI gets wrong.
On a Madison healthtech or research-tech build, AI handles the repetitive 70% — schemas, scaffolding, CRUD, dashboards, lab-data UI. The 30% AI gets wrong is the part Epic-trained engineers, validation teams, or IRBs immediately notice: PHI access without audit logging, EHR-integration shortcuts that fail at scale, FERPA-vs-HIPAA confusion on university-affiliated data, and bespoke research-tool conventions AI invents instead of reads. Raw AI output ships those silently.
We build for Madison operators — Epic-adjacent provider-side platforms, university and research-software teams shipping production code on top of research grants, insurance and claims tooling, B2B SaaS shipping into health-plan and provider buyers, and modernization of decades-old enterprise stacks. Our model: AI handles scaffolding and the repetitive 70%; a senior engineer owns architecture, security review, and signs off on every change.
AI writes the first draft. A senior engineer signs off.
Every change runs through review for security, tests, and architecture before it ships — that review is the product.
const draft = await ai.generate(spec) // minutes, not daysreview(draft, { security: true, tests: true, architecture: true })// ✗ rejected: PHI access without reason captured on an Epic-adjacent tool → reason + audit-log + access-policy test// ✓ merged: FERPA-safe role check on student-record endpoint, idempotent claims handlerOn a Madison healthtech or research build, the failure modes are missing PHI audit trails, FERPA-vs-HIPAA confusion, and non-idempotent claims handlers. Senior review catches them before a HIPAA review, an IRB, or a payer does.
What we build for Madison companies.
Healthcare & HIPAA-ready apps
Patient-facing portals, clinician tools, and care-coordination platforms built to HIPAA from day one.
EdTech & learning platforms
Student-facing apps, LMS extensions, and institutional tools that work for districts and universities.
SaaS platforms
Multi-tenant products with auth, billing, and dashboards — MVP to scale.
Modernization
Move legacy systems onto a modern, maintainable stack — incrementally, no big-bang.
AI applications
Copilots, RAG, search, and agents grounded in your data, with guardrails and evals.
Internal tools & copilots
Operations tooling that replaces the spreadsheet-and-tribal-knowledge workflow.
A senior team that moves at AI speed.
You work with senior engineers in Central Time who own architecture, regulated-data quality, and integration — fitting into an east-side healthtech standup, a downtown research-software cadence, or a west-side SaaS PR review — not a junior pool with raw AI output bolted on.
Madison's senior engineering pool is dominated by Epic and a smaller bench of insurance, ag-tech, and venture-backed startup employers — three-to-six months to hire and quietly poached by remote coastal roles. An AI-native team gets you shipping this week, flexes monthly, and doesn't need a Verona-corridor office.
Talk to an engineerTraditional Madison dev shop vs. AI-native.
| Traditional Agency | DEV.co (AI-native) | |
|---|---|---|
| Time to working software | Months | Days to weeks |
| Cost | Full senior rates, all hours | Lower — AI removes the rote work |
| Code quality | Good (if senior) | Same bar — every change reviewed |
| AI risk | — | Contained by senior review + tests |
| You own the code | Usually | Always — full repo on day one |
| Scales with you | Slow to staff up | Flex up or down monthly |
Common questions from Madison teams.
Do you work with Madison companies?
Do you build for HIPAA-scoped provider and Epic-adjacent systems?
Do you work with FERPA-scoped university and research data?
Is AI-built software production-ready?
Will we own the code?
How fast can we start?
Can you work with our existing team?
Let's build it — Madison.
Tell us what you're shipping. We'll give you a senior engineer's read, an honest timeline, a fixed quote, and tell you whether AI-native is the right fit for your build.