Databricks Machine Learning Services
Build, deploy, and scale machine learning models with Databricks ML. From AutoML to custom models, delivered by certified ML engineers.
Machine Learning Solutions We Build
ML Model Development
Build custom ML models for classification, regression, forecasting, and more
MLflow Implementation
Set up experiment tracking, model registry, and deployment workflows
AutoML Solutions
Implement automated machine learning with Databricks AutoML
Feature Engineering
Build feature stores and automated feature engineering pipelines
Model Deployment
Deploy ML models to production with monitoring and retraining
ML Pipeline Automation
End-to-end automated ML pipelines from data to predictions
Service Packages
ML Starter
- 1 ML model development
- MLflow setup
- Basic deployment
- Performance monitoring
- Documentation
- 30-day support
Enterprise ML
- 3 production ML models
- Feature store implementation
- Model registry & versioning
- Automated retraining
- A/B testing framework
- 3-month managed support
ML at Scale
- Complete ML platform
- Multi-model deployment
- Real-time inference
- Custom ML frameworks
- Team training program
- 6-month managed service
What's Included in Every Project
Data Analysis
Exploratory data analysis and feature discovery
Model Development
Training and optimizing ML models
MLflow Integration
Experiment tracking and model registry
Model Validation
Cross-validation and performance testing
Production Deployment
Model serving and inference endpoints
Monitoring Setup
Model performance and drift monitoring
Documentation
Model cards and technical documentation
Knowledge Transfer
Training for your ML team
60-Day Support
Post-deployment assistance
Our ML Development Process
Discovery
Business problem and data assessment
Modeling
Feature engineering and model training
Validation
Testing and performance optimization
Deployment
Production model serving
Monitoring
Performance tracking and retraining
Databricks ML Training for Your Team
Train your team to build and deploy ML models with Databricks through our expert-led courses.
Frequently Asked Questions
What is MLflow and why should we use it?
MLflow is an open-source platform for managing the ML lifecycle. It tracks experiments, packages code, manages models, and handles deployment—ensuring reproducibility, collaboration, and production-ready ML workflows.
What types of ML models can you build?
We build classification models (fraud detection, churn prediction), regression models (forecasting, pricing), recommendation systems, time series forecasting, anomaly detection, and custom deep learning models using TensorFlow, PyTorch, and scikit-learn.
How do you ensure ML models perform well in production?
We implement comprehensive monitoring for model performance, data drift detection, automated retraining pipelines, A/B testing frameworks, and shadow-sm deployments. This ensures models maintain accuracy and adapt to changing patterns.
What is Databricks AutoML?
AutoML automatically trains multiple models, performs hyperparameter tuning, and generates production-ready code. It's ideal for rapid prototyping and can achieve strong baseline performance, which we then optimize for your specific needs.
Build Intelligent Applications with ML
Get a free ML consultation. We'll assess your use case and design the right ML solution.