OpenAI Software / SaaS North America

Viable

Document Processing · Real-time Analytics

Viable has tackled this challenge by fine-tuning OpenAI’s LLMs to deliver fast and accurate insights from customer support interactions to recorded transcripts and everything in between, using GPT‑4 to analyze qualitative data on a scale that exceeds current techniques and performance. Viable’s platform provides...

Viable has tackled this challenge by fine-tuning OpenAI’s LLMs to deliver fast and accurate insights from customer support interactions to recorded transcripts and everything in between, using GPT‑4...
Viable's customers have saved nearly 1,000 hours per year , reduced support ticket volumes, and decreased customer churn since implementing their insights. "With Viable, we’ve been able to analyze...

Reported impact

Business outcome

Viable has tackled this challenge by fine-tuning OpenAI’s LLMs to deliver fast and accurate insights from customer support interactions to recorded transcripts and everything in between, using GPT‑4 to analyze qualitative data on a scale that exceeds current techniques and performance. Viable’s platform provides...

  • Customer Experience
  • Productivity Improvement

Solution

Viable has tackled this challenge by fine-tuning OpenAI’s LLMs to deliver fast and accurate insights from customer support interactions to recorded transcripts and everything in between, using GPT‑4 to analyze qualitative data on a scale that exceeds current techniques and performance. Viable’s platform provides companies with actionable insights to improve their Net Promoter Score (NPS), reduce support ticket volumes, and better inform their product roadmaps, all while saving on operating costs. Viable’s platform makes it effortless for customers to extract insights from their unstructured data in platforms like Zendesk, Intercom, Gong, and more through their seamless integrations, continuous syncing, and automated analysis.

Data flow

Viable’s platform makes it effortless for customers to extract insights from their unstructured data in platforms like Zendesk, Intercom, Gong, and more through their seamless integrations, continuous syncing, and automated analysis. In just a few clicks, the platform categorizes data into themes, and provides a week-over-week analysis to help customers understand the context behind their data, churn risk, and even the user profiles of those delivering that specific feedback.

Solution architecture

1 components · 1 layer
  1. Compute
    • GPT-4 Provides the reasoning layer used to generate and evaluate outputs.

Architecture clues

  • Provides the reasoning layer used to generate and evaluate outputs.
  • Viable has tackled this challenge by fine-tuning OpenAI’s LLMs to deliver fast and accurate insights from customer support interactions to recorded transcripts and everything in...
  • Viable's customers have saved nearly 1,000 hours per year , reduced support ticket volumes, and decreased customer churn since implementing their insights.
  • Viable’s platform makes it effortless for customers to extract insights from their unstructured data in platforms like Zendesk, Intercom, Gong, and more through their seamless...

Evidence from the source

"With Viable, we’ve been able to analyze unstructured data on a scale that was previously impossible,"
Viable has tackled this challenge by fine-tuning OpenAI’s LLMs to deliver fast and accurate insights from customer support interactions to recorded transcripts and everything in...
Viable's customers have saved nearly 1,000 hours per year , reduced support ticket volumes, and decreased customer churn since implementing their insights.
Viable’s platform makes it effortless for customers to extract insights from their unstructured data in platforms like Zendesk, Intercom, Gong, and more through their seamless...
Transparency Evidence & methodology 76/100 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 value76/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    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 scale5/10
    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
    4 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. OpenAI

    Viable customer story

    First-party
    https://openai.com/index/viable/
    Source type
    Vendor-published customer story
    Published
    Mar 18, 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 Mar 18, 2024 · OpenAI · 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.