Implementing Data Mesh Architecture for AI Teams: An Agency Delivery Guide A mid-market retail conglomerate with six brands came to an AI agency in Toronto with a familiar complain...
Version Control for Datasets and Training Data: How AI Agencies Manage Data Lifecycle An AI agency in Atlanta delivered a customer churn model to a SaaS company in Q1. The model pe...
Delivering Demand Forecasting for Supply Chains: The AI Agency Playbook A mid-size consumer goods company distributing 1,200 SKUs across 340 retail locations hired a five-person AI...
Building Intelligent Document Extraction Systems: The AI Agency Blueprint A commercial insurance underwriter was drowning in paper. Each new policy application required reviewing 1...
An agency built an energy optimization system for a commercial real estate portfolio that reduced energy costs by 23% across 47 buildings without any capital equipment upgrades. Here is the delivery playbook.
Event-Driven Architectures for AI Applications: How Agencies Deliver Reactive Intelligence An e-commerce agency in Seattle built a product recommendation engine for a fashion retai...
A healthcare ML agency improved their readmission prediction model from 72% to 89% AUC by rebuilding their feature engineering pipeline. No model architecture changes — just better features.
Building Fraud Detection Systems That Work: The AI Agency Field Guide A payments processor came to a seven-person AI agency in Miami after their rule-based fraud detection system f...
An agency burning $47,000 per month on GPU cloud costs reduced spending to $18,000 while increasing training throughput by 40%. Here is how they restructured their GPU cluster management.
Delivering Graph Neural Network Solutions: A Practical Guide for AI Agencies A cybersecurity firm came to a five-person AI agency in Boston with a problem their existing ML team co...
A retail agency built an image classification system handling 2.1 million product images daily across 847 categories with 95.3% top-1 accuracy. Here is the end-to-end delivery guide.
Building Image Segmentation Systems for Enterprise: The AI Agency Delivery Guide A manufacturing company approached a six-person AI agency in Detroit with a quality control problem...
An agency built an ML lead scoring system for a B2B SaaS company that increased sales conversion rates by 34% and reduced cost per acquisition by 28% within 90 days. Here is the full delivery playbook.
Evaluating LLM Performance for Client Deployments: Frameworks That Actually Work A six-person AI agency in Seattle built a customer support chatbot for a fintech client using GPT-4...
An agency fine-tuned a 7B parameter model for a legal firm that outperformed GPT-4 on their contract analysis tasks while running at 1/20th the per-query cost. Here is the full delivery guide.
Experiment Tracking and Reproducibility Best Practices for AI Agencies A two-person AI agency in Portland had a conversation that every agency has had at least once. The client cal...
An agency managing 23 production models for 8 clients had no model registry. A rollback that should have taken minutes took 11 hours. Here is how to build the registry that prevents that nightmare.
Orchestrating Complex ML Pipelines: Airflow, Kubeflow, and Beyond for AI Agencies An AI agency in San Francisco delivered a demand forecasting system to a grocery chain. The system...
A healthcare AI agency discovered their model API was leaking training data through carefully crafted queries. Here is the complete security hardening playbook for production ML systems.
A/B Testing ML Models in Production: The Agency Guide to Safe Deployments A fintech agency in San Francisco deployed an updated credit scoring model for a lending client. The new m...
Knowledge Distillation for Deploying Smaller Models: The Agency Efficiency Guide A retail analytics agency in Boston built a product recommendation engine for a major grocery chain...
Combining Multiple Models for Better Predictions: Ensemble Strategies for AI Agencies A two-person AI agency in Denver was on the verge of losing a $180,000 contract with a logisti...
An agency discovered their client's hiring model was 23% less accurate for candidates over 50. Here is how to build fairness testing into every stage of your ML pipeline.
Making Black-Box Models Explainable for Clients: The Agency Guide to Model Interpretability A healthcare AI agency in Philadelphia delivered a readmission risk model to a hospital ...
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