Vertex AI pilots need a data layer they can rely on.
Ingestion often gets rebuilt for every new source or customer, and transformations go untested. An agent built on top inherits every gap.
- Ingestion rebuilt for every new source or customer
- Untested transformations feeding reports
- Customer data separated by hand in multi-tenant setups
- GenAI pilots that never reach production
Built in your Google Cloud project.
We build BigQuery models and configuration-driven ingestion, tested and documented with dbt.
- BigQuery architecture and data modeling
- Pub/Sub and event-driven processing
- Secure multi-tenant analytics
We build the agent on Vertex AI and connect it to governed BigQuery data.
- Vertex AI, with Gemini or Claude
- Retrieval and document intelligence
- Evaluation and human review
Once it’s live, we monitor it, govern it and keep costs under control.
- Monitoring and data-quality checks
- Governance and cost control
- Fixes proposed as pull requests
From kickoff to your first use case in production on Google Cloud.
To onboard a new customer on a multi-tenant BigQuery platform, down from four weeks.
Everything runs in your Google Cloud project, and your data stays there.
Results in production
Questions we hear
Do you build multi-tenant analytics on BigQuery?+
Yes. We built a multi-tenant platform on BigQuery, Python, Mage and dbt, with isolated customer data products and a repeatable onboarding workflow.
Which models can the agent use?+
Gemini or Claude, both available on Vertex AI, chosen for the use case.
Does it work with our other clouds?+
Yes. We keep data contracts, transformation logic and operational interfaces clear enough to integrate with AWS, Snowflake, Databricks or on-premises systems.
Where does it run, and who controls it?+
Everything we build for you is yours: pipelines, data models, infrastructure code and documentation, in your own cloud account and repositories. Our agents and accelerators come with a licence that keeps working even if you stop working with us. If you need full source access, we offer that too.
What happens after the Sprint?+
You can run it yourself, extend it with a Build, or have us operate it with Managed.
Put your first use case into production on Google Cloud.
Tell us the use case and what you run on Google Cloud.