AI Case Studies: what buyers should look for

Enterprise AI

AI Case Studies: what buyers should look for

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Use these checks before you evaluate a case:

When a vendor says a system is live, it can mean a campaign, trial, phased rollout, or production. These are different levels of operational use.

When reading any case, use three checks:

  1. What public source supports the claim?
  2. What is the operating scope?
  3. What is clearly private?

1. Check the public source

Not every case has the same depth of published evidence.

External campaign source

Campaign material, event coverage, and other public content that supports a generative AI use case.

Examples on our site: Vinasoy and Enfagrow.

What you can trust:

  • customer name
  • campaign framing
  • top-line volume or reach when publicly shown

What may still be private:

  • infrastructure detail
  • workflow design
  • internal operating metrics

Public article + customer-approved material

A public article exists, and customer-approved material adds the rest.

Example on our site: CardX.

What you can trust:

  • company direction and use case are public
  • case is tied to a real named customer

What may still be private:

  • deeper KPI detail
  • regulated workflow specifics
  • architecture and rollout records

Customer-approved deployment material

Work has moved into customer-facing delivery, but no full public technical write-up is published yet.

Example on our site: GMA.

What you can trust:

  • rollout status is publicly verifiable
  • deployment moved beyond concept or demo

What may still be private:

  • usage metrics
  • internal screenshots
  • rollout depth by team or phase

Anonymized customer case

Real work where customer identity or operating details cannot be fully disclosed.

Example on our site: APAC aviation.

What you can trust:

  • the work is real
  • the operating scope is described conservatively

What may still be private:

  • customer name
  • architecture
  • performance detail

2. Check the operating scope

Deployment labels describe how far the work is integrated.

Campaign delivered

The campaign shipped and ran. This is common for consumer activations and personalized media experiences.

Trial deployment

The system is operating in a real customer setting at limited scale: more than a demo, not yet broad production.

Phase one rollout

Phase one is live. It does not mean the full roadmap is complete.

Production in customer environment

The workflow is running for real use inside the customer environment.

3. Check what stays private

Some details are public by design; others are not.

That usually includes:

  • customer-approved architecture summary
  • KPI and adoption direction
  • internal rollout records
  • infrastructure and IAM controls

That is normal in enterprise work. The key is clear boundaries between public and private detail.

A quick reader checklist

  • What public source supports this claim?
  • Is this a campaign, trial, phased rollout, or production system?
  • Does the case state where the system runs?
  • What details are explicitly kept private?