Stream data once - power dashboards today and ML tomorrow.
Ultree's Data & ML Workspace gives commerce, marketing, and ops teams one governed layer to analyze performance now and build predictive models later.
The Data & ML Workspace captures every key signal from storefronts, billing systems, and campaigns into a normalized, queryable data layer.
Purpose-built for teams transitioning from dashboards to ML, it delivers the flexibility to explore with SQL-like notebooks today while storing model-ready features for tomorrow.
Data flows once into a managed lake backed by PostgreSQL and DynamoDB for transactional joins, S3 for assets, and pgvector for embeddings. From there you can power Looker dashboards, run LLM-assisted forecasts, or experiment with Bedrock pipelines.
Every dataset is versioned, tagged, and evidence-ready, giving you reproducibility and audit trails as your data estate evolves.
Core capabilities for data-driven commerce teams
Replace siloed exports with a single system that serves analysts, operators, and ML practitioners alike.
Managed Data Lake
Stream product, order, catalog, and marketing data into warehouse-friendly formats without custom ETL.
Real-Time Ingestion
Kinesis and SQS streaming connectors keep dashboards and downstream models updated within minutes.
SQL-ish Workspace
Run ad-hoc queries, cohort analyses, and attribution checks in a notebook experience designed for ops teams.
Feature Store Foundations
Automatically extract, label, and store model-ready features for forecasting, personalization, and scoring.
AI & Vector Ready
Native support for pgvector, OpenSearch k-NN, and Pinecone to power semantic search and embeddings.
Governed Access
Tenant-scoped security, audit logging, and DPA compliance keep sensitive commerce data in check.
Analytics now, machine learning next
Chart daily performance in Looker or Mode, schedule evidence packs for stakeholders, and experiment with predictive models without re-architecting pipelines.
- Notebook to production workflows keep SQL analyses, dbt models, and feature stores aligned.
- Approval trails and data contracts ensure every model and dashboard can be rolled back or audited.
Outcomes that compound with every event
Analytics across commerce, billing, and marketing
Time-to-insight with streaming ingestion
Foundation for AI models and predictive pipelines
From dashboards to ML experiments