Custom software for Garland — built the AI-native way.
We pair senior engineers with an AI-accelerated delivery model to design, build, and ship custom software far faster than a traditional shop — without the fragile, unreviewed code that gives AI a bad name.
AI changed the economics of custom software. We rebuilt our process around it.
Garland anchors the northeast of the DFW metroplex — home to deep manufacturing and electronics employers (Kraft Heinz, Resistol, electronics OEMs), logistics demand, and growing B2B SaaS interest. Senior hires are six figures, months out, and picked over by DFW employers and the venture-backed challengers around them. AI changes the math, but only when senior people own the parts AI gets wrong.
AI is genuinely good at the repetitive 70% of software work: scaffolding, boilerplate, CRUD, first-draft UI, test stubs, glue code. It is dangerously unreliable at the other 30%: architecture, security, edge cases, and knowing when its own output is wrong. Teams that ship raw AI code learn this in production.
We build for Garland operators — manufacturing and shop-floor apps, logistics and distribution platforms, B2B SaaS shipping into mid-market 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: concurrent shop-floor write without atomic update → CAS + retry + concurrent-write test// ✓ merged: ordered-event reconstruction for late supplier EDI, idempotent tracking webhookOn a Garland manufacturing or logistics build, the failure modes are concurrent-write races, out-of-order supplier EDI, and non-idempotent tracking webhooks. Senior review catches them before a line stoppage or a chargeback does.
What we build for Garland companies.
SaaS platforms
Multi-tenant products with auth, billing, and dashboards — MVP to scale.
Supply-chain & ops platforms
Routing, dispatch, inventory, and visibility tools that replace clipboards and spreadsheets.
MES, IIoT & production software
Shop-floor systems, plant analytics, and supplier portals that connect old machines to new tools.
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 who own architecture and quality — not a junior pool with raw AI output bolted on. We communicate in Central Time and integrate with your tools and cadence.
Garland's senior engineering pool is part of the DFW-wide pool — 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 an office in downtown Garland.
Talk to an engineerTraditional Garland 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 Garland teams.
Do you work with Garland companies?
Can you integrate with legacy MES, ERP, and supplier-EDI systems?
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 — Garland.
Tell us what you're trying to ship. We'll give you an honest recommendation, a timeline, and a fixed quote — and tell you if AI-native is the right fit or not.