Custom software for Indianapolis — built the AI-native way.
We pair senior engineers with an AI-accelerated delivery model to ship custom software for Indianapolis's pharma, insurance, 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.
Indianapolis hosts a deep pharma and healthtech market (Eli Lilly), a strong insurance scene (Anthem, OneAmerica), and a fast-growing B2B SaaS cluster around the Salesforce ExactTarget acquisition and the venture-backed Indy startup bench. Senior hires are six figures, months out, and picked over by pharma, insurance giants, and the SaaS challengers around them. AI changes the math, but only when senior people own the parts AI gets wrong.
On an Indianapolis pharma, insurance, or SaaS build, AI handles the repetitive 70% — schemas, scaffolding, CRUD, dashboards, glue. The 30% AI gets wrong is the part that catches teams in regulated environments: missing audit trails on PHI, unsigned validated changes on pharma systems, claims-processing edge cases that fail at month-end, and integration with bespoke insurance core systems AI invents instead of reads. Raw AI output ships those silently.
We build for Indianapolis operators — pharma and biotech tooling, insurance and claims platforms, B2B SaaS shipping into mid-market and enterprise buyers, and modernization of decades-old enterprise stacks across the Crossroads of America. 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: validated change shipped without e-signature on a pharma tool → e-sig + audit + parameterized test// ✓ merged: idempotent claims-processing handler, ordered-event reconstruction for late insurance webhooksOn an Indianapolis pharma or insurance build, the failure modes are unsigned validated changes, non-idempotent claims handlers, and late-data corruption. Senior review catches them before a validator or a month-end run does.
What we build for Indianapolis companies.
Healthcare & HIPAA-ready apps
Patient-facing portals, clinician tools, and care-coordination platforms built to HIPAA from day one.
Insurance & claims platforms
Underwriting tools, claims automation, and broker portals for carriers and InsurTechs.
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 Eastern Time who own architecture, compliance posture, and quality on regulated work — fitting into a Lilly Center pharma team, a Carmel SaaS standup, or a downtown insurance PR review — not a junior pool with raw AI output bolted on.
Indy's senior engineering pool is concentrated around Eli Lilly, Anthem, and the Salesforce ExactTarget ecosystem — 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 Mass Ave office.
Talk to an engineerTraditional Indianapolis 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 Indianapolis teams.
Do you work with Indianapolis companies?
Do you build for GxP / pharma-grade environments?
Do you work with insurance core systems and claims platforms?
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 — Indianapolis.
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.