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BT Group

Customer Service Automation

BT Group needed to improve customer support across EE, BT, Business, Consumer, and internal contact channels by giving customers faster, more personalized answers while reducing the load on guides for routine issues such as travel support and billing queries.

Aimee now handles up to 60,000 customer conversations per week
Aimee's use has risen 51% year on year
Over 30 separate customer experiences have been defined within Aimee so far
automation success rates on several types of customer journey now approaching 50%

Reported impact

Business outcome

BT Group increased automated support volume and improved customer experience by using Aimee and generative AI to handle more conversations, explain billing charges more clearly, reduce live-chat demand for some journeys, and free guides to focus on more complex issues.

  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

BT Group rebuilt customer support around Sprinklr's unified customer experience platform, which sits behind EE's virtual assistant Aimee and the real-time online chat experience for EE and BT customers. When a customer seeks help, the platform draws on BT Group's data to generate personalised and accurate responses, including travel-support guidance and detailed billing explanations, and it can enrich conversations with product cards and carousels. BT hosts the AI capabilities on a private cloud instance and uses its internal Data Fabric platform to set data policies, privacy controls, and governance for the data used by the system. The architecture is LLM-agnostic, allowing BT Group to choose different large language models for different use cases while using the same contact platform to support customer interactions and free guides to focus on more complex cases.

Data flow

Customer questions arrive through Aimee or BT/EE online chat. Sprinklr's platform combines the interaction context with BT Group data to generate personalised answers, billing explanations, travel-support guidance, and rich media responses. The result is served back through chat, while harder cases are handled by guides. Data access is governed by Data Fabric, and the AI stack runs in a private cloud instance with safeguards to monitor misuse attempts.

Solution architecture

3 components · 3 layers
  1. Serving
    • Aimee Acts as EE's virtual assistant, handling customer conversations for support journeys such as international travel help and billing explanations.
  2. Orchestration
    • Sprinklr's unified customer experience platform Provides the customer contact platform that draws on BT Group data, powers Aimee, supports real-time chat, and delivers AI-enhanced sales and support experiences.
  3. Governance
    • Data Fabric Sets BT Group's internal data policies and governance controls for the data used by the AI capabilities.

Architecture clues

  • AI capabilities are hosted on a private cloud instance.
  • BT Group remains agnostic about which Large Language Model (LLM) it uses and can select the optimal LLM for each use case.
  • BT Group said the architecture will integrate with its new GenAI Gateway in the future.
  • Safeguards are in place to monitor attempts to get the AI to misbehave.

Evidence from the source

"AI capabilities are hosted on a private cloud instance, ensuring compliance with data and privacy regulations, and data policies are set by BT Group's internal data management platform, Data Fabric."
"BT Group has integrated Sprinklr's unified customer experience platform, meaning when a customer is seeking support, the platform can draw on BT Group's data to provide a personalised, accurate response."
"BT Group is transforming customer support through the integration of advanced AI and generative AI technologies, in collaboration with Sprinklr."
"BT Group remains agnostic about which Large Language Model (LLM) it uses in generative AI, continuing to draw on different LLMs."
"The customer contact platform, which powers EE's virtual assistant Aimee, also provides the messaging capability for real-time online chat with customers."
"the Gen AI-enhanced experience within Aimee which helps customers prepare for international travel has halved the need for online chat/messaging support"
"~60,000 conversations per week are now handled through Aimee compared to ~30,000 per week just two years ago."
Transparency Evidence & methodology 100/100 reference value · 94% 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 value100/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    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 impact25/25
    4 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence94%
  • Source authority25/25
    The deployment is described by the adopting organization or a government source.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    7 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • 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. BT Group

    BT Group customer story

    First-party
    https://newsroom.bt.com/bt-group-leans-on-ai-to-transform-customer-service-experience/
    Source type
    Customer-published story
    Published
    Dec 12, 2024
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page Dec 12, 2024 · BT Group · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.