I build private, production-grade AI systems for regulated environments. Your data stays in your VPC. Compliance requirements get met. And the platform actually works at scale.
I work with organizations that can't use public cloud APIs. Maybe it's regulatory constraints (GDPR, HIPAA, FCA). Maybe it's data sensitivity. Or maybe it's cost at scale. My work covers three areas:
Every model update goes through a gold-set evaluation. If precision drops below your SLO, it doesn't deploy. No vibes, just metrics.
I deploy on Kubernetes with proper GPU scheduling (MIG when appropriate), autoscaling, and cost telemetry. Your infrastructure, your control.
Grafana dashboards tracking precision/recall over time, p95 latency, cost per request, and drift detection. You can't improve what you don't measure.
Full audit logs, encryption at rest and in-transit, SBOM generation for vulnerability tracking, and no data leaving your environment.
I choose tools based on your constraints, not the latest hype. That said, here's what I reach for most often:
If you're building private AI systems and need someone who's done it before, let's have a conversation.