The PI.EXCHANGE AI & Analytics Engine (the Engine) is a Data Science and Machine Learning (ML) platform that empowers everyone, even novice users, to affordably build high-performance ML applications in minutes or hours, not weeks or months.

The easy-to-use connected toolchain provides everything you will need to go from raw data to predictions and insights within a single pipeline. Manual and repetitive machine learning tasks are automated, and the Engine's intelligent features help guide the user end-to-end. So, whether you are building a small pilot project with no dedicated data science resources, or are deploying large-scale enterprise ML systems, you can equip your existing team with the right tool to build meaningful solutions, fast. The Engine gives users the flexibility to customize their ML pipeline from scratch for classification, regression, time-series, or clustering problems or to select an ML solution template to develop their ML application. While both ML development options are guided and require no-coding experience, the latter requires only articulation of business requirements and problem context via a few key steps - everything else is taken care of.

Notable AI solutions include: Customer Churn Prediction Leveraging your manufacturing data to build predictive maintenance strategies Predict online fraudulent transactions and reduce false positives and; Optimize logistics decision-making

Decode GA4 is a BigQuery-native data transformation utility built for teams working with the Google Analytics 4 BigQuery export. GA4 writes event data into deeply nested RECORD and ARRAY structures. Reading a single field such as pagelocation or pagetitle requires a correlated UNNEST subquery, repeated for every field an analyst needs, on a wildcard table that scans every partition. Decode GA4 does that transformation once, properly, and exposes the result as direct columns. The same query becomes simple dot-notation SQL against one predictable table per property.

It is a connector, not a platform. Decode GA4 is subscribed through Google Cloud Marketplace and delivered as a linked dataset via BigQuery Analytics Hub, so it deploys into your existing Google Cloud project and runs on your own BigQuery compute. Your data never leaves your project, there is no egress, and your existing IAM, security and data residency controls still apply.

Processing is metadata-driven and incremental. Each date partition is processed exactly once unless GA4 modifies it upstream, in which case the affected partitions are detected and reprocessed automatically. When GA4 adds new event parameters the output adapts without a full rebuild, so downstream dbt, Dataform and SQLMesh models keep working. Transformed data can be written as compressed Parquet in Cloud Storage and read through external tables, which cuts storage cost and enables export to AWS S3 or Azure Blob Storage.

Pricing is usage-based through Google Cloud Marketplace, from $50 per GiB for the first GiB down to $0.50 per GiB above 500 GiB. There is no subscription and no monthly minimum. Typical cost is $1.50 to $8 a month for sites under 10,000 monthly sessions, billed on your existing Google Cloud invoice.