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OpenAI Public Sector North America

State of Minnesota Enterprise Translation Office

Customer Service Automation · Document Processing

the top three major non-English languages (opens in a new window) spoken in the state. Language gaps in government communication are a challenge for community health, safety, and trust.

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For government services to be truly effective, they must be accessible to all residents. Removing language barriers is essential to high quality public service.
Rapid turnaround times: What once took weeks to complete can now be done in under 48 hours, with urgent translation requests fulfilled in as little as 2 hours. Since the beta launch, the ETO has...

Reported impact

Business outcome

For government services to be truly effective, they must be accessible to all residents. Removing language barriers is essential to high quality public service.

  • Compliance
  • Customer Experience
  • Productivity Improvement

Solution

the top three major non-English languages (opens in a new window) spoken in the state. Language gaps in government communication are a challenge for community health, safety, and trust. The ETO works to ensure equitable access to government information and resources for all, bridging linguistic gaps to ensure a stronger, more inclusive Minnesota. To address these issues, the ETO began using AI, incorporating ChatGPT as a key pillar of their solution to provide translation services faster, more accurately, and more equitably. The ETO collaborated closely with the Transparent Artificial Intelligence Governance Alliance (TAIGA), Minnesota’s IT Services program, to ensure the program followed safe, ethical, and transparent AI principles.

Data flow

To address these issues, the ETO began using AI, incorporating ChatGPT as a key pillar of their solution to provide translation services faster, more accurately, and more equitably. The ETO collaborated closely with the Transparent Artificial Intelligence Governance Alliance (TAIGA), Minnesota’s IT Services program, to ensure the program followed safe, ethical, and transparent AI principles.

Solution architecture

1 components · 1 layer
  1. Orchestration
    • custom GPTs Package prompts, instructions, and curated context for repeatable internal tasks.

Architecture clues

  • Beyond translation accuracy, the ETO’s ChatGPT‑enabled workflow also optimizes for cultural relevance to ensure government messaging is both accessible and inclusive.
  • Package prompts, instructions, and curated context for repeatable internal tasks.
  • The program’s success led to a full rollout in July, just four months after the beta launch, with all ETO team members trained to utilize ChatGPT for translation work.
  • To address these issues, the ETO began using AI, incorporating ChatGPT as a key pillar of their solution to provide translation services faster, more accurately, and more...

Evidence from the source

Beyond translation accuracy, the ETO’s ChatGPT‑enabled workflow also optimizes for cultural relevance to ensure government messaging is both accessible and inclusive.
The program’s success led to a full rollout in July, just four months after the beta launch, with all ETO team members trained to utilize ChatGPT for translation work.
To address these issues, the ETO began using AI, incorporating ChatGPT as a key pillar of their solution to provide translation services faster, more accurately, and more...
the top three major non-English languages (opens in a new window) spoken in the state.
Transparency Evidence & methodology 71/100 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 value71/100
  • 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 scale0/10
    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

    State of Minnesota Enterprise Translation Office customer story

    First-party
    https://openai.com/index/state-of-minnesota/
    Source type
    Vendor-published customer story
    Published
    Sep 17, 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 17, 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.

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