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Citi Wealth

Customer Service Automation

Citi Wealth wanted to reduce the friction of clients navigating apps, calls, and meetings by giving U.S. wealth clients real-time, personalized access to market insights, opportunity prompts, and advisor-supported financial guidance.

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Reported impact

Business outcome

Citi Wealth expects Citi Sky to create a more intuitive, responsive, and personalized wealth experience, help clients access insights and act on opportunities, and extend the reach and impact of financial advisors.

  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

Citi Wealth built Citi Sky as an always-on advisor-assisting wealth agent on Google Cloud's AI stack. The implementation uses Gemini Enterprise Agent Platform as the environment for building, scaling, governing, and optimizing the agent, with Gemini models supplying the reasoning and financial guidance layer. To create a multimodal virtual persona, Citi combined Google DeepMind's real-time avatar technology with Gemini's Live API so clients can interact through low-latency voice, audio, and video conversations in English and Spanish. The agent is being integrated into Citi Wealth platforms in the U.S. to work alongside financial advisors, drawing on grounded internal wealth data such as Chief Investment Office market insights and CD maturity prompts. The release does not name storage products, but it says interactions are built on a secure, grounded data foundation designed for regulatory compliance.

Data flow

Citi Wealth client interactions in English or Spanish enter Citi Sky through voice, avatar, audio, and video interfaces powered by Gemini's Live API and Google DeepMind's real-time avatar technology. Gemini models running on Gemini Enterprise Agent Platform combine market insights from Citi Wealth's Chief Investment Office and event triggers such as CD maturity prompts on a secure, grounded data foundation, then return personalized guidance into Citi Wealth platforms for clients and financial advisors.

Solution architecture

5 components · 3 layers
  1. Compute
    • Google Cloud Provides the cloud infrastructure underpinning Citi Sky and the broader AI stack used for deployment.
    • Gemini models Power the agent's financial guidance, multimodal reasoning, and conversational intelligence.
  2. Serving
    • Google DeepMind's real-time avatar technology Powers the Citi Sky virtual persona used in real-time conversational interactions.
    • Gemini's Live API Enables seamless, low-latency audio and video conversations between clients and Citi Sky.
  3. Orchestration
    • Gemini Enterprise Agent Platform Serves as the unified environment for building, scaling, governing, and optimizing the enterprise agent.

Architecture clues

  • Built as an always-on AI-powered member of the Citi Wealth team.
  • Interactions are built on a secure, grounded data foundation for regulatory compliance.
  • Launch supports English and Spanish, with additional languages planned over time.
  • Phased rollout to Citigold clients in the U.S. beginning in summer 2026.
  • Uses low-latency audio and video conversations for multimodal interaction.

Evidence from the source

"Citi Sky is aimed at reshaping how clients in the U.S. access market insights, act on opportunities, and engage with their financial advisors."
"Citi Sky was developed using the Gemini Enterprise Agent Platform and will be integrated over time into Citi Wealth platforms in the U.S. to work alongside financial advisors"
"For decades, managing your financial life meant navigating apps, calls, and meetings. With Citi Sky, you simply ask – and act."
"Interactions are being built on a secure, grounded data foundation and designed to be in compliance with regulatory standards."
"Launching in English and Spanish, Citi Sky is designed to scale to additional languages over time."
"using Google DeepMind's real-time avatar technology and Gemini's Live API to enable seamless, low-latency audio and video conversations."
Transparency Evidence & methodology 71/100 reference value · 92% 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 value71/100
  • 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 specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence92%
  • 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
    6 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 specificity8/10
    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. Citi Wealth

    Citi Wealth customer story

    First-party
    https://www.citigroup.com/global/news/press-release/2026/citi-wealth-unveils-citi-sky-ai-powered-member-google-cloud-deepmind-technologies
    Source type
    Customer-published story
    Published
    Apr 22, 2026
    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 Apr 22, 2026 · Citigroup · 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.

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