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Microsoft Financial Services United States

PIMCO

Document Processing · Enterprise Knowledge Search · Sales Automation

The client-facing teams at PIMCO serve hundreds of thousands of clients around the world, all of whom need accurate, up-to-date information on the products they hold. To boost the client experience, PIMCO wanted to help its associates spend less time aggregating data and more time engaging with clients.

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Finding those answers may mean searching through a large number of data sources, depending on the request. This process, when accounting for the high volume of clients across the organization
PIMCO is a global leader in active fixed income with $2 trillion in assets under management (as of September 30, 2024). For over 50 years

Reported impact

Business outcome

PIMCO is a global leader in active fixed income with $2 trillion in assets under management (as of September 30, 2024). For over 50 years

  • Compliance
  • Productivity Improvement
  • Revenue Growth
  • Scalability

Solution

The client-facing teams at PIMCO serve hundreds of thousands of clients around the world, all of whom need accurate, up-to-date information on the products they hold. To boost the client experience, PIMCO wanted to help its associates spend less time aggregating data and more time engaging with clients. To help associates find relevant information faster, PIMCO built an enterprise tool, named ChatGWM, on Azure AI. ChatGWM is a secure, RAG-based application that searches across PIMCO-approved structured and unstructured data sources to deliver fast, relevant information to its teams. Instead of searching through documents themselves, associates can now simply type their questions into ChatGWM using advanced search technology to get more insightful responses, fast. ChatGWM also provides the source of its information, helping associates verify that everything is factually correct.

Data flow

Source content is gathered from the organization's documents and knowledge repositories, Azure OpenAI Service interprets or generates responses from that content, and the resulting answers or assessments are surfaced to employees or citizens through the application workflow.

Solution architecture

4 components · 3 layers
  1. Compute
    • Azure OpenAI Service Runs the large-language-model features for classification, summarization, retrieval, or conversational responses in the solution.
    • Azure AI Services Supplies pretrained AI capabilities such as vision, language, or speech inside the business workflow.
  2. Storage
    • SharePoint Acts as the collaboration and content-management layer for enterprise knowledge and documents.
  3. Serving
    • Azure AI Search Indexes enterprise content and retrieves relevant passages for AI-powered search and answer experiences.

Architecture clues

  • Azure AI Search: Indexes enterprise content and retrieves relevant passages for AI-powered search and answer experiences.
  • Azure AI Services: Supplies pretrained AI capabilities such as vision, language, or speech inside the business workflow.
  • Azure OpenAI Service: Runs the large-language-model features for classification, summarization, retrieval, or conversational responses in the solution.
  • Instead of searching through documents themselves, associates can now simply type their questions into ChatGWM using advanced search technology to get more insightful responses
  • SharePoint: Acts as the collaboration and content-management layer for enterprise knowledge and documents.
  • To help associates find relevant information faster, PIMCO built an enterprise tool, named ChatGWM, on Azure AI.

Evidence from the source

Finding those answers may mean searching through a large number of data sources, depending on the request. This process, when accounting for the high volume of clients across the organization
Instead of searching through documents themselves, associates can now simply type their questions into ChatGWM using advanced search technology to get more insightful responses, fast.
PIMCO is a global leader in active fixed income with $2 trillion in assets under management (as of September 30, 2024). For over 50 years
The client-facing teams at PIMCO serve hundreds of thousands of clients around the world, all of whom need accurate, up-to-date information on the products they hold.
To help associates find relevant information faster, PIMCO built an enterprise tool, named ChatGWM, on Azure AI. ChatGWM is a secure
Transparency Evidence & methodology 86/100 reference value · 89% 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 value86/100
  • 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 impact15/25
    1 metric describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence89%
  • 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 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. Microsoft

    PIMCO customer story

    First-party
    https://www.microsoft.com/en/customers/story/19744-pimco-sharepoint
    Source type
    Vendor-published customer story
    Published
    Feb 6, 2025
    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 Feb 6, 2025 · Microsoft · 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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