Global pharmaceutical company
AI agents that finally had one place to look
Before
Ambitious AI agents running on fragmented data. Data scientists calling different APIs to feed each agent, with a large amount of manual work in between and no single version of the truth.
After
Data foundations rebuilt on Google Cloud with BigQuery as the warehouse and single source of truth. Models and agents stopped hunting across systems for the right data — one governed place to query, at scale.
Google CloudBigQueryAgent-ready data layer
Global marketing and advertising group
One view of campaign performance, not twelve
Before
Campaign, performance and marketing data spread across separate systems, with each team assembling its own view and no consistent picture of how campaigns were actually performing.
After
A unified data foundation on Google Cloud covering campaign management, performance and wider marketing data. One governed layer, one set of definitions, and reporting the business could act on without reconciling it first.
Google CloudBigQueryMarketing data platform
UK broadcast and telecoms operator
Outages fixed before customers noticed them
Before
Network telemetry arriving faster than anyone could use it. Capacity planning ran on lagging reports, and outages were handled reactively — found when customers noticed, not before.
After
A streaming platform turning raw telemetry into operational intelligence: real-time ingestion into BigQuery, feeding capacity planning and predictive models that flagged likely network failures early enough to fix them before customers were affected.
Pub/SubDataflowBigQuery
Storage Transfer ServiceStreaming data platform