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Secure AI virtual data roomsCustom 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?
More from DEV.co
Madison teams usually need more than one kind of build. These are the practices behind the work above.
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.