Case studies a technical buyer will believe

The parts that make it believable

A case study a technical buyer believes names the customer, describes the workload in enough detail to compare with their own, gives the scale, states what was measured before and after and how, admits what did not work, and carries a date. Remove any one of those and the piece reads as a testimonial, which an engineer skims for the logo and forgets.

Many infrastructure case studies fall short on the second and fourth. They say "AI workloads" where they should say what model was trained or served, and they report a percentage improvement with no baseline. A buyer cannot map that to anything.

The reader is usually an engineer asked to check whether a vendor is credible before a manager signs. They are looking for a reason to say no. A case study that hands them the details lets them say yes with something to point at, and that is the job it has to do.

The workload, described like a ticket

Write the workload the way an engineer would describe it in a ticket. Fine-tuning a model of a stated size at a stated precision. Serving a named open model to an internal tool with a stated context length. Batch embedding of a document archive overnight. The buyer reading it wants to know within a paragraph whether this is their problem.

Name the hardware exactly: card, form factor, memory, count. The H100 SXM 80GB and the L40S 48GB are different machines for different jobs, and "GPU cluster" hides which one this was. The memory alone tells a reader a lot. A 70 billion parameter model in 16-bit needs about 140 GB for its weights, before the key-value cache, so a reader can check whether the setup described could have held it.

Give the scale in units an engineer counts: cards, nodes, hours of training, requests a day, size of the dataset. "Large-scale" is an adjective; a node count is a fact, and it tells the reader whether your experience covers a job of their size.

Before and after, with the method

A before-and-after claim needs both halves measured the same way. If the customer moved from another provider, say what they ran there, on what card, and how the comparison was made. If the gain came from a software change rather than the hardware, say so, because a buyer moving the same workload to you without that change will not see it.

Report the cost side honestly. A faster job on dearer hardware may cost more per run, and an engineer will do that arithmetic whether you do or not. Rates for one card differ between sellers; the H100 SXM page shows the current spread, and a reader will check yours against it.

What did not work

Include at least one thing that went wrong: a first configuration that ran out of memory, a migration that took longer than planned, a region that had no capacity for the first week. It is the section marketing would have cut, which is why a technical reader looks for it.

It also answers the question a buyer is really asking: what will go wrong for me? A case study that says the customer hit a driver problem and how it was fixed is more useful than three paragraphs of praise.

Keep it specific. "There were some initial challenges" is the sentence that marks a section written to tick a box. Name the challenge, how long it took, and whose fix it was.

Written by the engineer, edited by marketing

The best source for a technical case study is the customer engineer who did the work, interviewed for an hour with the transcript kept. Their words carry the details marketing would smooth away: the flag that had to be set, the job that was split in two, the week lost to a quota. Edit for length and clarity, and leave the details in.

Quotes should say something a reader can use. "The team was great to work with" tells an engineer nothing. "We moved the training job over in two days because the image we already had ran unchanged" tells them what to expect, and they can ask you whether theirs will too.

Let the customer read the draft and correct it. A case study the customer has signed off is one they will stand behind when a prospect calls them, and that call is one of the reasons to write a case study at all.

Named, dated and checkable

A named customer with a named engineer who will take a call carries more weight than any anonymous one. If the customer will not be named, say so and say why, and describe them precisely enough to be credible: a research lab, a fintech running fraud models. "A leading enterprise" is no description.

Date it, and say what has changed since. Infrastructure moves fast enough that a case study from two hardware generations ago describes a different product. A line at the top saying "written in March, on the hardware and software of that month" lets the reader adjust.

If the case study makes a claim a buyer might want to verify, link the evidence. A claimed listing can add what only the vendor knows, with a source, through the vendor workspace, and the same standard of sourcing serves a case study. The post on benchmark method lists what a performance claim needs beside it.