David Lapsley, Ph.D.

CTO, ActualyzeAI

Welcome!

Hi, I’m Dave! With 25+ years building infrastructure platforms at AWS, Cisco, and now as CTO of ActualyzeAI, I help enterprises navigate the journey from AI proof-of-concept to production deployment. This blog shares battle-tested patterns, real-world case studies, and practical strategies for the 13% of AI projects that actually make it to production.

Why 87% of AI projects fail isn’t a technical problem—it’s a planning problem. Let’s fix that.

Current Projects

NVIDIA DGX Spark Hardware Research

Comparing NVIDIA’s integrated AI platform ($3,999) against DIY open-source GPU infrastructure. 8-week testing series covering setup time, performance, cost, and developer experience.

Topics: Hardware comparison, model serving, local AI infrastructure

Tampa Bay Enterprise AI Community

Monthly meetups bringing together CTOs, platform engineers, and business leaders to discuss production AI infrastructure challenges.

Next Event: November 14, 2025 - “Hands-On: Building Production AI Infrastructure with KServe”

Join the community:

Meetup Group Slack Community

Enterprise AI Infrastructure

Production deployment patterns, Kubernetes for AI workloads, GPU cost optimization, hybrid cloud architectures, and infrastructure that scales from POC to production.

AI Governance & Compliance

HIPAA, SOX, GDPR compliance for AI systems. Data sovereignty, model governance, audit trails, and risk management frameworks for regulated industries.

Cost Optimization & ROI

GPU utilization strategies, spot instance management, resource allocation, chargeback models, and TCO analysis for cloud vs. on-premises AI infrastructure.

MLOps & Platform Engineering

KServe, KubeFlow, model serving, CI/CD for ML, monitoring, multi-tenancy patterns, and building production-grade AI platforms.

Upcoming Content

November 2025: Hands-On KServe Workshop

Step-by-step guide to deploying production AI infrastructure with KServe in 60 minutes. Complete deployment automation scripts and Kubernetes manifests included.

Topics covered:

  • Kubernetes cluster + GPU Operator setup
  • Istio + Knative installation
  • KServe deployment and configuration
  • GPU-accelerated InferenceService deployment
  • Monitoring with Prometheus, Grafana, and DCGM