◆ MLOPS × HEALTHTECH

MLOps development for healthtech

Training, eval, deployment, monitoring of ML and LLM systems. Reproducible runs, drift detection, cost-aware inference. Tuned for healthtech — HIPAA-aware, audit-trail-first builds. Patient data, consent flows, EHR integrations, wearable data pipelines.

◆ WHY MIR

Why teams pick us

Healthtech-grade engineering

HIPAA-aware, audit-trail-first builds. Patient data, consent flows, EHR integrations, wearable data pipelines.

MLOps where it counts

Training, eval, deployment, monitoring of ML and LLM systems. Reproducible runs, drift detection, cost-aware inference.

Senior team, no pyramid

9+ years building outsourced product teams. Every engineer is a senior shipping production code — not a 5-person team with one architect on top.

◆ HEALTHTECH PAIN POINTS WE SOLVE

Where MLOps meets healthtech

HIPAA + GDPR overlap done correctly

We've shipped this in production. We design for it from day one — not as a retrofit.

Consent + audit logs from day one

We've shipped this in production. We design for it from day one — not as a retrofit.

EHR / FHIR integrations without vendor lock-in

We've shipped this in production. We design for it from day one — not as a retrofit.

PII isolation under regulatory review

We've shipped this in production. We design for it from day one — not as a retrofit.

◆ STACK

What we build with

Modal / RunPod / AWS Weights & Biases / MLflow DVC / LakeFS Triton / vLLM Prometheus + custom drift checks
◆ PROCESS

How we ship

  1. Reproducibility first — frozen envs, pinned data, lineage tracking.
  2. Eval harness before any production rollout.
  3. Canary + shadow deploys for every model update.
  4. Drift + cost dashboards from day one.
◆ START A PROJECT

Tell us what you're building

We respond within 24 hours. NDA available on request.