Senior engineers who build and run the systems DME providers bill, document, and get paid with — backend, interface, and the servers underneath. One missing document is the whole margin. We write the code that catches it.
One missing document. That is the entire distance between a paid claim and a write-off.
Not case studies written after the fact. Software our engineers wrote code inside, still running in providers' offices. We name a client only with their permission, so the products below are described, not identified.
Enterprise HME/DME platform
The cloud software providers run their businesses on — documentation, inventory, delivery, resupply, patient billing, and revenue cycle management — serving thousands of practices across the United States.
AI record review for DME
AI review that flags missing documentation before the claim is submitted. Verifies coverage-policy compliance, extracts patient and physician data from unstructured records, and auto-generates payer-compliant addendums.
Consumer sports platform
A performance platform for athletes and coaches. The same rigor we bring to regulated systems, applied to a consumer product with real-time demands and no tolerance for lag.
The compliance engine plugs straight into the billing platform. We have worked on both sides of that seam — which is rarer than it sounds, and is precisely where healthcare integrations go wrong.
A claim moves through four stages. Each one is a place it can die. We have written code in all four.
Intake, structured extraction from messy medical records, and LCD/NCD verification before anything is submitted.
Clean-claim rules, payer-specific edits, and the validation that decides whether a claim is even accepted.
Denial handling, reason-code logic, appeals, and the addendums that turn a rejection back into a payment.
Posting, reconciliation, and reporting — so the money that arrives matches the money you were owed.
Multi-tenant systems, REST APIs, and service boundaries that survive a growing product. Laravel and Python, because we know them cold.
MySQL, PostgreSQL, Redis, Elasticsearch. Query optimization and replication for data that stopped fitting in memory long ago.
AWS, Docker, CI/CD, zero-downtime deploys. A deploy that scares you is a deploy you postpone.
Latch Vector is a team of senior engineers, and it is those same engineers you work with directly — the people writing your code, not a layer in front of it.
We deliver complete systems and maintain them in production: the backend, the interface, and the infrastructure beneath it. From architecture and deployment through the ongoing maintenance that follows, one team is accountable end to end, and the team grows as the work does.
Our deepest domain is the demanding side of healthcare — the systems that determine whether a durable medical equipment provider is paid. We understand what an LCD is, why a claim returns CO-50, and what fails when a resupply workflow meets a real patient record. That expertise is a specialty, not a limit: the same engineering applies wherever data is regulated or volume is significant.
If you need engineers who have solved your problem before, and who stay engaged as the work scales, we are worth an hour of your time.
No account managers, no middlemen between you and the engineers.
Senior Engineer
System design, service boundaries, and the multi-tenant data models healthcare platforms are built on. Laravel and Python in production for 7+ years.
Senior Engineer
Claims, documentation pipelines, and integrations with established DME platforms. Fluent in the rules that turn a valid record into a paid claim.
Senior Engineer
Cloud infrastructure, containerization, and CI/CD. Keeps deploys boring and keeps the systems handling PHI locked down and auditable.
Chosen because we know them cold, not because they were trending.
The things engineers and operators actually ask us first.
We work inside systems more often than we start them. Most of our work has been adding to and untangling billing, documentation, and revenue cycle code that was already in production with real patients in it. Greenfield is fine too — but "there is an existing codebase and it scares people" is our normal starting condition.
Access control and audit trails as a default, not a phase two. We assume every record is PHI, scope access to it, and log who touched what. We have built inside systems that carry protected health information for thousands of US practices, so this is habit rather than a checklist we discover at the end.
Yes — that is most of what we do. We read unfamiliar code for a living: payer-specific edits, reason-code logic, resupply workflows, the parts a previous team left undocumented. We map it before we touch it, and you get the map.
Probably, if the data is regulated or high-volume. The domain we know cold is healthcare billing, but the engineering — multi-tenant architecture, integrations, performance, audit trails, the interface on top — travels. We have shipped a real-time consumer platform on the same foundations.
Laravel and Python on the backend, Vue and React on the interface. MySQL, PostgreSQL, Redis, and Elasticsearch for data. AWS, Docker, and CI/CD for infrastructure and deployment. We reach for tools because we know them cold, not because they are trending — the full list is above.
Describe what is breaking, what is slow, or what will not survive an audit. You will get an engineer's answer, not a sales call.
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