About Recs Studio

Recs Studio helps mid-to-large retailers and B2B marketplaces deliver state-of-the-art personalised recommendations without building an internal ML platform from scratch. We combine production-grade recommender systems, modern data engineering, and cloud infrastructure into a managed service that our customers can deploy in hours.

Our Mission

Every retailer sits on rich customer and product data, but most never turn that data into real-time, personalised experiences because the path from raw data to a production recommender is long, expensive, and error-prone. Our mission is to shorten that path to a single managed platform: connect your data, configure your model, deploy your endpoints, and continuously improve accuracy.

What We Built

Recs Studio is a complete recommendation platform built on TensorFlow Recommenders (TFRS) and TFX production pipelines. It covers the full lifecycle:

• Data ingestion: ETL from SQL, NoSQL, data warehouses, and cloud storage into a managed data warehouse.
• Feature engineering: Visual schema builder, two-tower feature assignment, embeddings, normalisation, cyclical encoding, and cross features.
• Model architecture: Configurable retrieval, ranking, and multitask models with dense, dropout, batch-normalisation, and regularisation layers.
• Experiments: Quick-test pipelines to validate configurations before full training.
• Training: GPU-powered production training, model registry, automated evaluation, and scheduled retraining.
• Serving: Auto-scaling endpoints with TF Serving and ScaNN, real-time monitoring, and client SDK examples.

Get in Touch

For partnerships, press, or general inquiries, email us at support@recs.studio. To see the platform in action, click the Request a Demo button.