AWS Select Tier Consulting PartnerAI & Machine Learning
Build production ML models that solve real business problems
From predictive analytics to computer vision — we build, deploy, and maintain ML solutions that deliver measurable ROI.
Challenges We Solve
87% of ML projects never make it to production. We fix that.
Models That Don't Deploy
Your data science team builds great notebooks, but models never make it to production.
Poor Model Performance
Models work in testing but fail in production with real-world data drift and edge cases.
Unclear ROI
Hard to quantify the business value of ML investments or prioritize use cases.
Talent Gap
Building an in-house ML team is expensive and takes years to mature.
What We Build
End-to-end ML solutions on Amazon SageMaker.
Predictive Analytics
Forecast demand, predict churn, score leads, and anticipate equipment failures. Turn historical data into future insights.
Computer Vision
Automate visual inspection, document processing, object detection, and image classification for your business.
Natural Language Processing
Extract meaning from text — sentiment analysis, entity recognition, document classification, and semantic search.
Recommendation Systems
Personalize customer experiences with product recommendations, content suggestions, and next-best-action engines.
Why Choose PATHSDATA
85%+ Model Accuracy
Rigorous feature engineering and validation for models that actually work.
3-6 Month Delivery
From use case to production model with our proven methodology.
Production Ready
Not just notebooks — deployed, monitored, and maintained models.
Measurable ROI
Clear metrics and business outcomes tied to every model.
Proven Results
Retail
Demand forecasting that reduced inventory costs by 20% and stockouts by 35%.
Financial Services
Credit risk scoring with 40% improvement in default prediction accuracy.
Healthcare
Patient readmission prediction enabling proactive intervention programs.
Manufacturing
Predictive maintenance reducing unplanned downtime by 45%.
Technology Stack
Platform
- Amazon SageMaker
- SageMaker Studio
- Feature Store
Frameworks
- PyTorch
- TensorFlow
- scikit-learn
- XGBoost
AWS AI Services
- Rekognition
- Textract
- Comprehend
- Personalize
Data
- S3
- Glue
- Athena
- Feature Store
Our Process
Problem Framing
Define the business problem, success metrics, and data requirements. Ensure ML is the right solution.
Data Preparation
Clean, transform, and engineer features. Build reproducible data pipelines for training and inference.
Model Development
Experiment with algorithms, tune hyperparameters, and validate performance with proper holdout sets.
Deploy & Monitor
Production deployment with real-time monitoring, retraining triggers, and performance alerts.
Ready to Put ML to Work?
Let's identify high-impact ML opportunities and build models that deliver real business value.