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Microsoft Software / SaaS United States

Perplexity.AI

Enterprise Knowledge Search

Perplexity.AI is the creator of Perplexity Ask, a revolutionary AI-based conversational answer engine that combines large language models with a robust semantic search engine. As a typical startup—with a lean staff and a leaner budget—the company needed a platform for Perplexity Ask that would support fast time to market, serve as a force multiplier for that lean staff, scale to support millions of users, and deliver security and reliability at a cost-effective price. It found what it was searching for in Azure AI Studio.

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About 70 percent of Perplexity Ask users are in the business sector.
Adding ChatGPT 4.0 via Azure OpenAI Service doubled throughput from 300,000 tokens per minute to 600,000, with latency declining by 30 percent.
Massive scalability at a less-than-massive price The answer engine currently serves 7 million users per month.
That’s an important differentiator of Azure AI Studio: we had our first prototype in hours.” Discover more details CUSTOMER Perplexity.AI PRODUCTS Azure Azure Operator Call Protection ORGANIZATION SIZE 1-49 employees COUNTRY United States BUSINESS NEED Artificial Intelligence INDUSTRY Other Professional Services Explore related stories Stories in this industry Stories about this customer Showing 32 of 98 categories Showing 1-2 of 2 slides Previous slide Next slide We are Microsoft Empowering others Our mission is to empower every person and every organization on the planet to achieve more.

Reported impact

Business outcome

“Azure AI Studio improved the experience for creating AI products. We found it mapped perfectly to our needs for faster development and time to market, and greater throughput, scalability, security, and trust.” Denis Yarats, Chief Technology Officer and Cofounder, Perplexity.AI Far more than they bargained for Aravind Srinivas and his partners didn’t realize at first that they were creating a groundbreaking, AI-based conversational answer engine.

  • Cost Reduction
  • Customer Experience
  • Scalability
  • Speed to Market

Solution

Perplexity.AI used Azure OpenAI Service, Azure AI Studio, Microsoft Dynamics 365 to surface grounded answers from enterprise knowledge faster. Perplexity.AI is the creator of Perplexity Ask, a revolutionary AI-based conversational answer engine that combines large language models with a robust semantic search engine. As a typical startup—with a lean staff and a leaner budget—the company needed a platform for Perplexity Ask that would support fast time to market, serve as a force multiplier for that lean staff, scale to support millions of users, and deliver security and reliability at a cost-effective price. It found what it was searching for in Azure AI Studio. Key implementation elements included Azure OpenAI Service generates natural-language responses and task automation for the solution; Azure AI Studio provides the workspace for building, testing, and deploying the AI application; Microsoft Dynamics 365 provides the common business process layer that standardizes operations;...

Data flow

Enterprise content from documents, meetings, websites, or internal systems is passed through retrieval and model services so users receive grounded answers inside the target workflow.

Solution architecture

4 components · 2 layers
  1. Compute
    • Azure OpenAI Service Generates natural-language responses and task automation for the solution.
    • Azure AI Studio Provides the workspace for building, testing, and deploying the AI application.
    • Microsoft Azure Hosts the application, data, and integrations on scalable cloud infrastructure.
  2. Orchestration
    • Microsoft Dynamics 365 Provides the common business process layer that standardizes operations.

Architecture clues

  • Emphasizes secure enterprise access to data and AI capabilities.

Evidence from the source

About 70 percent of Perplexity Ask users are in the business sector.
It found what it was searching for in Azure AI Studio.
Massive scalability at a less-than-massive price The answer engine currently serves 7 million users per month.
Perplexity.AI is the creator of Perplexity Ask, a revolutionary AI-based conversational answer engine that combines large language models with a robust semantic search engine. As a typical startup—with a lean staff and a leaner budget—the company needed a platform for Perplexity Ask that would support fast time to market, serve as a force multiplier for that lean staff, scale to support millions of users, and deliver security and reliability at a cost-effective price. It found what it was searching for in Azure AI Studio.
“Azure AI Studio improved the experience for creating AI products. We found it mapped perfectly to our needs for faster development and time to market, and greater throughput, scalability, security, and trust.” Denis Yarats, Chief Technology Officer and Cofounder, Perplexity.AI Far more than they bargained for Aravind Srinivas and his partners didn’t realize at first that they were creating a groundbreaking, AI-based conversational answer engine.
Transparency Evidence & methodology 100/100 reference value · 92% confidence · 2 sources

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
    2 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence92%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability23/25
    11 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 transparency9/10
    2 source references 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

    Perplexity.AI customer story

    First-party
    https://www.microsoft.com/en/customers/story/1701944358715641785-perplexity-ai-azure-partner-professional-services-usa
    Source type
    Vendor-published customer story
    Published
    Nov 15, 2023
    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
  2. LinkedIn

    Perplexity | LinkedIn

    Third-party
    https://www.linkedin.com/company/perplexity-ai/

    The public company page includes numberOfEmployees value 1408 and a PostalAddress with streetAddress 115 Sansome St, addressLocality San Francisco, and addressCountry US.

    Source type
    structured profile
    Supports
    • Company size

Date evidence

  • Published on source page Nov 15, 2023 · Microsoft · First-party
    Open date source
Not separately sourced Industry, Region. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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