What challenges did The Stakeholder Company face before AI implementation?

Information overload and fragmented global signals across tools, notes, and email made it difficult to maintain shared institutional memory and connect news to specific stakeholders.

What was the impact of the AI solution?

Improved interactive query latency by 20%. Delivered sub-10-second insights across millions of global data points. Maintained more than 99.99% platform uptime.

Source

GCPPilotEvidence: Medium65/100

The Stakeholder Company (TSC): Gemini + Vertex AI 'Ask Genie' co-pilot for stakeholder sensing with BigQuery

Use case typeConversational analyticsUpdated Jun 23, 2026

The Stakeholder Company (TSC) built Genie, a cloud-native intelligence platform that unifies global media signals and proprietary stakeholder data for Fortune 500 and other clients. The platform uses BigQuery as a primary data warehouse and vector store, Gemini in Vertex AI for conversational reasoning, and GKE-based microservices to deliver a secure AI co-pilot for strategic dialogue with data. The system links real-time signals across 95 countries and millions of stakeholder data points to support evidence-based decision making.

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Organization: The Stakeholder Company
Industry: Professional Services
Location: United States
Published: June 2026

Reported outcomes

Interactive query latency: −20%

Time & speed

Catalog median for time & speed deployments: −50% across 295 reported metrics. Compare benchmarks →

Planned next steps

The source says the pilot could deliver: Created a secure AI co-pilot for strategic dialogue with data.

Why do we believe this?Outcome claims, sources, and evidence checks

Normalized claim

Interactive query latency: 20% decrease

Google Cloud Customer StoriesJun 23, 2026Customer storyExplicit claimMedium evidence strength

achieved a 20% improvement in query latency

Normalized claim

Platform uptime: 100% increase

Google Cloud Customer StoriesJun 23, 2026Customer storyExplicit claimMedium evidence strength

ensured a 99.99% platform uptime

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: The Stakeholder Company
Provider: GCP
Maturity: Pilot
Linked source: Google Cloud Customer Stories

The platform uses BigQuery as a primary data warehouse and vector store, Gemini in Vertex AI for conversational reasoning, and GKE-based microservices to deliver a secure AI co-pilot for strategic dialogue with data

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 2 of 2

1Conversational analytics
2Executive analytics

Built Genie as a proactive sensing system, workflow orchestration layer, and AI co-pilot.
Used BigQuery for large-scale entity extraction and as a vector store, Gemini in Vertex AI for Ask Genie conversational reasoning, AlloyDB for PostgreSQL for stakeholder analytics, and GKE microservices for the platform architecture.

Technologies

Gemini BigQuery AlloyDB for PostgreSQL Vertex AI Google Kubernetes Engine Cloud KMS Cloud Run Pub/Sub

Improved interactive query latency by 20%.
Delivered sub-10-second insights across millions of global data points.
Maintained more than 99.99% platform uptime.

Architecture

TSC migrated from a legacy database setup to a high-performance microservices environment on Google Kubernetes Engine. BigQuery serves as the primary data warehouse and vector store for entity extraction at scale. Gemini in Vertex AI powers the Ask Genie conversational co-pilot, while AlloyDB for PostgreSQL supports stakeholder analytics. Sensitive AI workflows remain within the Google Cloud perimeter, secured with Cloud KMS.

Sources & evidence1

Evidence: Medium65/100Evidence strength