Data Infrastructure for AI
Build scalable data pipelines and infrastructure for AI/ML workloads with robust ETL and real-time processing
The Foundation of Great AI
AI models are only as good as the data they're trained on. We build robust data infrastructure that ensures your ML models have access to clean, validated, and timely data — from ingestion to feature engineering.
Data Engineering Solutions
Data Pipeline Design & ETL
Build scalable ETL/ELT pipelines for ML workflows with Airflow, Prefect, and modern orchestration tools.
Real-time Data Processing
Stream processing for live ML inference and real-time analytics with Kafka, Flink, and Spark Streaming.
Data Lake Architecture
Design modern data lake solutions with Delta Lake, Iceberg, and cloud-native storage for ML data.
Cloud Data Infrastructure
Deploy on AWS, Azure, or GCP with Terraform, CloudFormation, and infrastructure as code.
Data Quality & Validation
Ensure data quality and validation with Great Expectations, dbt tests, and custom monitoring.
Feature Stores
Centralized feature management for ML with Feast, Tecton, and custom feature stores.
Data Engineering Services
Data Pipeline Development
End-to-end pipeline creation
Data Infrastructure Setup
Cloud-native data infrastructure
Data Warehouse Design
Modern data warehousing for analytics
Modern Data Architectures
Lambda Architecture
Batch + real-time processing
Kappa Architecture
Stream-first architecture
Medallion Architecture
Bronze, Silver, Gold layers
Data Mesh
Domain-oriented ownership
Data Engineering Tools
Orchestration
Processing
Storage
Quality
Build Data Infrastructure That Scales
Let's create data pipelines that power your AI initiatives.