We design, implement, and operate scalable ML systems and data infrastructure that accelerate product-led growth and reduce time-to-value.
We bridge research and engineering to deliver production ML and data systems. Our team combines applied ML, cloud engineering, and product-first design to embed intelligence into business workflows.
CI/CD for models, containerized inference, feature stores, and automated rollout strategies to keep models healthy in production.
Robust, observable pipelines and data contracts that power analytics and ML at scale across real-time and batch workloads.
Feature engineering, embeddings, recommendation systems, and APIs tailored to your product metrics and SLAs.
Problem framing, metrics, and feasibility.
Architecture, data contracts, and experiments.
Engineering, model training, and API delivery.
Monitoring, retraining, and continuous improvement.
Increased engagement by 24% via real-time recommendations and A/B-driven rollout.
Unified pipelines and reduced ETL costs by 40% while improving SLAs.
Implemented drift detection and automated retrain flows to maintain accuracy over time.