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IBM Media and Entertainment United States

UFC

Real-time Analytics

UFC needed to scale fight insight generation across more than 40 live events a year without depending solely on manual research and domain experts to analyze fast-changing performance data.

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3x estimated increase in insight volume
40% estimated reduction in query generation time
more than 40 live events annually

Reported impact

Business outcome

UFC reduced the time needed to generate insights, tripled the volume of available content signals and gave its editorial teams a scalable way to enrich fan storytelling across events.

  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

IBM and UFC built the UFC Insights Engine to automate how fight stories and statistics are generated for broadcast, digital and social teams. IBM watsonx Orchestrate sits at the center as the pre-fight insights agent and routing layer, enabling researchers to ask natural-language questions through a unified conversational interface. Behind that experience, IBM built text-to-SQL pipelines for structured queries and retrieval-augmented generation pipelines using IBM Granite and Llama models for grounded responses. IBM watsonx.ai helps identify the key performance indicators that influence fight outcomes, while watsonx.data provides vectorized storage and retrieval and watsonx.governance supports explainability, relevance scoring and transparency. Terraform automates deployment of UI and API components. Together, these components transform fight statistics, athlete profiles and event history into reusable insight workflows that scale content creation across the UFC calendar.

Data flow

Historical fight statistics, athlete profiles and event outcomes are queried through text-to-SQL and RAG pipelines, grounded in watsonx.data, and then routed by watsonx Orchestrate to generate insights and narratives for UFC content teams.

Solution architecture

5 components · 4 layers
  1. Compute
    • IBM watsonx.ai Extracts and generates contextual fight insights from historical data and matchup statistics.
    • IBM Granite Provides one of the grounded LLM options used in the RAG pipelines behind the Insights Engine.
  2. Storage
    • IBM watsonx.data Stores and retrieves vectorized fight and athlete data used to ground responses.
  3. Orchestration
    • IBM watsonx Orchestrate Acts as the orchestration and conversational layer for UFC’s pre-fight insights agent.
  4. Governance
    • IBM watsonx.governance Adds explainability, relevance scoring and transparency to AI-generated responses.

Architecture clues

  • Deployment pipeline automates UI and API infrastructure
  • Supports broadcast, digital and social workflows from a single interface
  • Uses both text-to-SQL and RAG pipelines

Evidence from the source

At the core of the solution is IBM® watsonx Orchestrate® , which begins with a pre-fight insights agent that facilitates the process.
This orchestration integrates advanced tools, such as text-to-SQL pipelines for structured data queries and retrieval-augmented generation (RAG) pipelines powered by ... IBM Granite® and Llama.
Time to generate insights was reduced by an estimated 40%.
Transparency Evidence & methodology 100/100 reference value · 84% 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
    2 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence84%
  • 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 evidence15/20
    3 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. IBM

    UFC customer story

    First-party
    https://www.ibm.com/case-studies/ufc
    Source type
    Vendor-published customer story
    Published
    Jul 8, 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

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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