Carro
Explore Project
Streaming, analytics infra
Core Capacities
Data pipeline
Project Focus
Real-time, AI-ready
Scale of Impact
2025
Year
Overview
1
Carro’s production database was carrying both customer operations and analytics, creating performance bottlenecks as the platform scaled. The team wanted to move beyond basic reporting toward real-time insights, machine learning, and AI, but needed a modern data infrastructure that could handle growth without straining production systems.
2
Sierra Studio designed a decoupled streaming pipeline that replicated production data in real time using Kafka CDC. Instead of analytics jobs running against live systems, data flowed into a dedicated Databricks environment, where it was cleaned, structured, and enriched. This separation gave Carro the ability to pursue advanced analytics and AI without slowing down day-to-day operations.
3
Sierra began by analyzing and documenting Carro’s existing systems, then built the pipeline with scalable, cloud-based components. Real-time ingestion through Kafka ensured no impact on production, while Databricks handled tiered data enrichment and distributed processing with Spark. Infrastructure was defined in Terraform for repeatability, and AI tools were used to accelerate code migration and ensure accuracy.
