OpenAI Healthcare Europe

Genmab

Document Processing · Enterprise Knowledge Search

As a company that has recently tripled in size, Genmab wanted to use AI to address operational challenges—and develop new ways of working with vast amounts of complex scientific data.

3.5 hours average time savings per week
As part of its strategic vision to innovate and leverage AI, Genmab identified a unique opportunity to partner with ChatGPT by launching its Enterprise offering and rolling it out to 1,000 employees....
Genmab recently launched an innovative project to transform the creation of clinical trial documents , including clinical study reports (CSRs), patient safety narratives, and investigational new drug...
In a recent survey, employees reported that ChatGPT Enterprise saves them an average of 3.5 hours per week , and many could not imagine performing aspects of their jobs without these newfound...

Reported impact

Business outcome

As part of its strategic vision to innovate and leverage AI, Genmab identified a unique opportunity to partner with ChatGPT by launching its Enterprise offering and rolling it out to 1,000 employees. Now, less than a year later, they’ve launched "AI Everywhere" to give ChatGPT access to almost everyone at the...

  • Productivity Improvement
  • Scalability

Solution

As a company that has recently tripled in size, Genmab wanted to use AI to address operational challenges—and develop new ways of working with vast amounts of complex scientific data. Genmab now has more than 100 custom GPTs that help with everything from drafting documents, summarizing scientific literature to simple and advanced analytics of data. The recent release of GPT‑4o’s vision enhancements has enabled Genmab to tackle tasks that were impossible even just three months ago. Specifically, the model now interprets complex documents containing images, text, and numbers in a human-like manner. This advancement offers a new, more efficient approach to verifying factual references in medical affairs publications, reducing the significant time and costs previously required for this process.

Data flow

The recent release of GPT‑4o’s vision enhancements has enabled Genmab to tackle tasks that were impossible even just three months ago. Specifically, the model now interprets complex documents containing images, text, and numbers in a human-like manner.

Solution architecture

3 components · 3 layers
  1. Compute
    • GPT-4o Extracts, interprets, and reasons over multimodal or unstructured inputs inside the workflow.
  2. Serving
    • ChatGPT Enterprise Provides a governed assistant environment for employees working across the deployment’s core workflows.
  3. Orchestration
    • custom GPTs Package prompts, instructions, and curated context for repeatable internal tasks.

Architecture clues

  • Extracts, interprets, and reasons over multimodal or unstructured inputs inside the workflow.
  • Genmab now has more than 100 custom GPTs that help with everything from drafting documents, summarizing scientific literature to simple and advanced analytics of data.
  • Genmab recently launched an innovative project to transform the creation of clinical trial documents , including clinical study reports (CSRs), patient safety narratives, and...
  • Provides a governed assistant environment for employees working across the deployment’s core workflows.
  • The recent release of GPT‑4o’s vision enhancements has enabled Genmab to tackle tasks that were impossible even just three months ago.

Evidence from the source

As a company that has recently tripled in size, Genmab wanted to use AI to address operational challenges—and develop new ways of working with vast amounts of complex scientific...
Genmab now has more than 100 custom GPTs that help with everything from drafting documents, summarizing scientific literature to simple and advanced analytics of data.
Genmab recently launched an innovative project to transform the creation of clinical trial documents , including clinical study reports (CSRs), patient safety narratives, and...
The recent release of GPT‑4o’s vision enhancements has enabled Genmab to tackle tasks that were impossible even just three months ago.
Transparency Evidence & methodology 91/100 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 value91/100
  • 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 impact25/25
    2 metrics 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
    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

    Genmab customer story

    First-party
    https://openai.com/index/genmab/
    Source type
    Vendor-published customer story
    Published
    Sep 19, 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 Sep 19, 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.