ML Architecture Services | mlai.qa - Sprint Services
mlai.qa's ML architecture sprint services - ML strategy, architecture review, MLOps foundation, data pipeline design, model selection, and ML platform engineering.
ML Strategy & Roadmap
90-day ML plan, stack decisions, build-vs-buy analysis, and team structure recommendations - the strategic foundation before you commit to an architecture.
ML Architecture Review
Independent audit of your existing or planned ML stack - architecture diagram, bottleneck analysis, and a prioritised fix list. The fastest way to know what to change.
MLOps Foundation Sprint
CI/CD for ML, experiment tracking, model registry, and deployment pipeline design - the operational foundation that lets your team ship models like they ship code.
Data Pipeline Architecture
Ingestion, transformation, feature engineering, and storage layer design - a scalable data architecture that feeds your models reliably at any volume.
Model Design & Selection
Framework selection, training approach, fine-tuning vs RAG decision, and benchmark methodology - the model architecture decisions that define your system's ceiling.
ML Platform Engineering
Scalable model serving infrastructure, monitoring, drift detection, and A/B testing for models - the platform layer that keeps your ML system reliable in production.
Build ML that scales.
Book a free 30-minute ML architecture scope call with our experts. We review your stack and tell you exactly what to fix before it breaks at scale.
Every engagement is scoped by our principal architect, Adrian Vale: 20+ years in production engineering, 40+ professional certifications. Meet Adrian
Talk to an Expert