AI & MLOps Case Studies
Real-world AI & MLOps case studies: what happened in production, the architecture behind it, the numbers and the lessons to take to your own team.
Air Canada's Chatbot Hallucination: How a RAG Support Bot Created Legal Liability in Production
Air Canada's support chatbot invented a bereavement fare policy that didn't exist; a tribunal held the airline liable. The lesson: LLM outputs need guardrails and legal accountability before going to production.
AI & MLOps · beginner · 12 min read
How a B2B SaaS Team Cut LLM API Spend by 65% with Model Routing, Prompt Caching, and Request Batching
A 120-engineer SaaS company slashed monthly LLM costs from $41k to $14k by routing cheap models for simple tasks, caching repeated prompts in Redis, and batching async jobs — without degrading user-facing quality.
AI & MLOps · intermediate · 12 min read
How a B2B SaaS Team Cut LLM Inference Costs by 71% by Moving to Self-Hosted vLLM
A 120-engineer SaaS company replaced OpenAI API calls with self-hosted Mistral on vLLM, cutting per-query cost by 71% and p99 latency by 40% after a painful but instructive migration.
AI & MLOps · advanced · 12 min read
How a B2B SaaS Team Cut Model Deployment Time from 3 Days to 4 Hours with MLflow and Kubeflow
A 120-engineer SaaS company replaced ad-hoc notebook deployments with MLflow tracking and Kubeflow Pipelines, cutting deployment time by 93% and eliminating silent model regressions.
AI & MLOps · intermediate · 12 min read
How a B2B SaaS Team Cut Prompt Regression Escapes by 94% with an Automated LLM Eval Pipeline in CI
A 120-engineer SaaS company wired LLM output evaluation into their CI pipeline using pytest, LangSmith and GitHub Actions, catching prompt regressions before they reached production.
AI & MLOps · intermediate · 12 min read
How a B2B SaaS Team Took a RAG Support Assistant from Demo to Production
A 120-engineer SaaS company rebuilt their RAG support bot's retrieval pipeline, added an eval harness and guardrails, and cut hallucination-related escalations by 68%.
AI & MLOps · intermediate · 12 min read
How a Feature Store Eliminated Training-Serving Skew and Cut Model Errors by 34%
A B2B SaaS company's recommendation model silently degraded because training and serving computed features differently. Adopting Feast on Redis fixed the skew and cut prediction errors by 34%.
AI & MLOps · advanced · 12 min read
How a Fintech Team Caught Silent Fraud-Model Drift Before It Cost Them $2M
A fraud model degraded silently for six weeks before anyone noticed. The team built a drift-detection and auto-retraining pipeline that cut false-negative fraud losses by 61%.
AI & MLOps · intermediate · 12 min read
How a Shared Kubernetes Cluster Raised GPU Utilisation from 25% to 70%
A B2B SaaS company's ML platform team tripled effective GPU utilisation by combining time-slicing, bin-packing, and a fair-share queue — without buying a single new node.
AI & MLOps · advanced · 12 min read