Google Cloud Telecommunications Canada

TELUS

Customer Service Automation · Data Lake / Data Warehouse Modernization · Enterprise Knowledge Search

TELUS needed to unify siloed customer and network data so teams could trust the same foundation for generative AI, launch new services faster, and scale agentic platforms without each business unit building its own disconnected stack.

90% of AI model traffic runs through Gemini Enterprise Agent Platform
created hundreds of millions of dollars in business value through data and AI enablement

Reported impact

Business outcome

TELUS improved data trust, sped AI rollout, and created a reusable agentic platform that supports everything from customer experience to future secure identity and self-healing network services.

  • Productivity Improvement
  • Risk Reduction
  • Scalability

Solution

TELUS used Google Cloud to create a unified enterprise data and AI foundation centered on BigQuery and Gemini Enterprise Agent Platform. BigQuery became the shared source of truth for customer information and other operational data, supported by services such as Cloud SQL, BigQuery Analytics Hub, and Knowledge Catalog to improve sharing, discoverability, and governance. On top of that data layer, TELUS built Fuel iX on Google Cloud and now routes most AI model traffic through Gemini Enterprise Agent Platform, using Model Garden to access Gemini, Claude, and other models from one managed environment. Gemini Enterprise Customer Experience extends the same platform into customer service, while the broader data foundation gives TELUS room to build secure identity services and self-healing network capabilities. The outcome is a more trusted, reusable AI platform where data unification and model flexibility reinforce each other instead of living in separate programs.

Data flow

Customer and network data is unified in BigQuery and shared through governance services such as Analytics Hub and Knowledge Catalog. Fuel iX and other AI services on Gemini Enterprise Agent Platform consume that data, and Gemini Enterprise Customer Experience applies the same foundation to customer-facing use cases.

Solution architecture

7 components · 5 layers
  1. Compute
    • Gemini Supplies core reasoning capabilities inside TELUS's agentic AI services.
  2. Storage
    • BigQuery Provides TELUS's unified enterprise data foundation for customer, network, and AI workloads.
    • Cloud SQL Supports operational data services around the shared TELUS platform.
  3. Serving
    • Gemini Enterprise Customer Experience (CX) Extends the unified AI platform into TELUS customer-service use cases.
    • BigQuery Analytics Hub Improves governed data sharing across the enterprise.
  4. Orchestration
    • Gemini Enterprise Agent Platform Hosts Fuel iX and routes most AI model traffic through a governed multi-model environment.
  5. Governance
    • Knowledge Catalog Improves data discoverability and governance on top of the BigQuery foundation.

Architecture clues

  • Analytics Hub and Knowledge Catalog sit alongside BigQuery
  • Fuel iX was built on Google Cloud
  • Model Garden is used to access Gemini, Claude, and other models
  • Unified customer and network data is intended to support self-healing networks

Evidence from the source

90% of AI model traffic runs through Gemini Enterprise Agent Platform
Because BigQuery unifies and secures customer data, TELUS can now easily launch new services
By moving to Google BigQuery and creating one unified data foundation for customer information across the enterprise ... we increased the trust in the data
TELUS built its generative AI platform, Fuel iX™, on Google Cloud
With unified customer and network data in BigQuery ... TELUS is now working to build and scale self-healing networks
Transparency Evidence & methodology 80/100 reference value · 79% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value80/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact15/25
    1 metric describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence79%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Google Cloud

    TELUS customer story

    First-party
    https://cloud.google.com/customers/telus-bigquery
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes

Date evidence

  • First archived Jul 23, 2026 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    Open date source
  • Sitemap last modified Jul 22, 2026 · Google Cloud · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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