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.
Talk to an Expert