Software and AI engineering services
Eight things we build, two ways to buy them.
MacroCoderz builds AI agents, retrieval-augmented generation systems, model integrations and workflow automation. You can buy that as a fixed-scope project from $4,500, or as a dedicated engineer embedded in your team at $2,800 per month. Everything is built in your repos, and you own all code and prompts from the first commit.
- US-registered - Colorado
- 50+ clients
What we build
MVP development
Web, mobile, SaaS and AI MVPs, fixed scope.02Hire dedicated developers
Front-end, back-end, mobile and AI, monthly.03AI staff augmentation
Embedded engineers on your team, monthly.04AI integration services
AI inside the product you already have.05AI product development
Zero to a working product.06RAG systems
Retrieval over your own documents and data.07AI agent development
Agents that plan, act and self-correct.08AI workflow automation
Automation wired into your existing stack.Building for your own client rather than yourself? The same work, delivered under your brand, is white-label AI development.
Which shape of engagement fits
| Project build | Dedicated pod | White-label | |
|---|---|---|---|
| You have | A defined outcome and a deadline | A roadmap and no AI experience in-house | A client who asked for AI |
| Price | From $4,500, fixed | $2,800/engineer/month | Fixed per project |
| You manage | Nothing day to day | The engineer, like your own | The client relationship |
| Commitment | Until handover | Rolling monthly, 30 days notice | Per project |
| Read more | Project builds | Dedicated pods | White-label |
How we work, whichever you pick
Every build ships with an evaluation harness, not just code. That means a labelled test set, regression runs on every prompt change, and agreed thresholds for what counts as good enough to ship - the part that decides whether a system still works in month six.
You own the output completely: source, prompts, eval data, infrastructure definitions and documentation, from the first commit. Model and cloud spend goes on your accounts at cost rather than being resold with a margin. See pricing for the full breakdown and security for data handling, subprocessors and retention.
Proof is on the case studies: a multi-tenant retrieval platform at 68% lower query latency, and an agent with an 87% first-loop repair rate.
Tell us what you are building
A free strategy session: what is buildable, what it costs, what we would do first.