Publicis Sapient delivers end-to-end Machine Learning solutions on Google Cloud, guiding clients through the entire MLOps lifecycle and helping them achieve measurable business value from their data. We help clients build, deploy, and scale production-grade ML systems. We leverage the full power of Google's ecosystem, from data engineering in BigQuery and Dataflow to custom model development in Vertex AI.
 

Discover more about our specialized ML services below.

Data Engineering & Feature Management for ML

A successful model begins with high-quality, enterprise-ready data. We establish the foundational data pipelines required for sophisticated ML, performing deep data exploration, preprocessing, and feature engineering at scale. We leverage Google Cloud's powerful data suite including BigQuery for analysis, Dataflow for stream and batch preprocessing, and Dataproc for large-scale data transformation to create the robust, model-ready datasets that fuel accurate predictions.

Custom Model Development on Vertex AI

We guide clients through the complete ML development lifecycle on the Vertex AI Platform. Our teams handle every stage, from initial model training and hyperparameter tuning to rigorous bias and variance analysis and model evaluation. Using Vertex AI Notebooks and Vertex AI Training, we build and refine custom models tailored to your unique business challenges, ensuring they are not only powerful but also fair, explainable, and robust.

Applied ML with Google Cloud APIS

For established use cases, we accelerate business outcomes by leveraging Google’s powerful pre-trained Machine Learning APIs. This allows for rapid deployment without extensive custom model development. We help clients turn unstructured data into actionable intelligence by implementing Document AI for intelligent document processing, the Cloud Vision API for image analysis, the Cloud Natural Language API for text understanding, and the Speech-to-Text API for transcription services.

MLOps & Scalable Model Deployment

We establish robust MLOps foundations to automate the deployment, monitoring, and retraining of your models at scale. Using Vertex AI Pipelines, Cloud Build, and Cloud Composer, we create CI/CD/CT (Continuous Training) systems that securely and efficiently move models from experimentation to production. We ensure high-performance online prediction by deploying models to optimized endpoints and by leveraging hardware accelerators (GPU, TPU) as needed.