Technology explainer videos connect unfamiliar systems with decisions people need to make. They can introduce a scientific concept, show a production process or help developers move into a new platform.
By
Larry Mutenda
| What are the best technology explainer video examples? Strong technology explainer video examples include Fujitsu for hospital scheduling, IBM for a hard concept, Intel for how a chip is made, Amazon Web Services for category education, Google Search Central for public information and Cloudflare for developer onboarding. |
Technology explainer videos are short videos that explain systems, products and concepts most people cannot see. They range from scientific ideas to chip manufacturing and developer platforms. The viewer’s starting knowledge decides where the video begins.
This article looks at six technology explainer videos from Fujitsu, IBM, Intel, Amazon Web Services, Google Search Central and Cloudflare. For each one, I describe what the video covers, who it speaks to and what other technology companies can take from it. After the examples, I cover explaining architecture without diagram overload and visual metaphors for technical concepts. Then I explain how to plan your own technology explainer video.
A hospital executive, a beginning computing student and an experienced developer do not start with the same knowledge. These examples show how much the entry point changes even when every subject is technical.
Here is a quick overview of the six videos in this article, grouped by how each company uses the video. The table links to each example below.
We picked videos that each show a different job a technology explainer can do: a business decision, a hard concept, how a product is made, category education, public information and developer onboarding.
The lead example, Fujitsu, comes from the Creamy Animation video library. The other five videos are published on each company’s own YouTube channel and were publicly available when we checked them in October 2026. We describe each video from its own content and description, and we credit any figures to the company that published them.
| # | Company | Use |
|---|---|---|
| 1 | Fujitsu | Lead example: hospital scheduling technology |
| 2 | IBM | Explaining a hard concept |
| 3 | Intel | How a product is made |
| 4 | Amazon Web Services | Category education |
| 5 | Google Search Central | Public information |
| 6 | Cloudflare | Developer onboarding |
How does a hospital test a different operating room schedule without changing the live one? Fujitsu uses that operational question to give its recommendation engine and digital twin a concrete purpose. The technology matters because of the decision it supports.
Fujitsu’s hospital scheduling video appears in the video library of Creamy Animation.
Fujitsu’s video describes a surgical scheduling solution developed with Baptist Health South Florida. The subject is relevant to hospital perioperative executives who need to make better use of operating room schedules. The video centres on a decision. It does not start with the algorithm in isolation.
According to the video, the recommendation engine analyzes block utilization using a hospital’s own scheduling data. It suggests changes while accounting for surgeon, equipment and staff availability. Those constraints give the technical video a practical purpose. The technology buyer can understand why a recommendation involves more than finding an empty slot.
The video also describes a Generative Block Scheduling Wizard and a digital twin. These allow users to test possible changes without altering live schedules. The video reports a 37% improvement in available prime-time operating room minutes over three months in hospital trials.
I consider this kind of video for a solution page or a discussion with operational decision-makers. Its runtime is 3:20. That gives the topic more room than a brief category introduction. The lesson is the connection between data, constraints and a decision. Other technology companies can build that connection before asking the audience to understand the machinery behind their product.
Someone familiar with everyday computers encounters quantum computing for the first time. They need to understand what makes it different before a list of components will mean much. A concept lesson can begin with that comparison and then build the technical account.
Without a clear point of comparison, familiar computer terminology can create misleading assumptions. IBM uses the difference between quantum and traditional computers as its entry point. That is a different route from Fujitsu’s hospital example, which begins with an operational decision. Both give technical detail a reason to appear before the audience has to remember the components.
Jessie Yu describes how quantum computers differ from traditional computers and walks through five key elements. The seven-minute video serves people learning the subject rather than buyers assessing one application. Starting with the distinction between systems gives the component discussion a foundation.
A customer knows what a microprocessor does but has little sense of how it is made. The finished chip hides the production sequence. A manufacturing video can connect the familiar object with the material and work behind it.
Intel starts from sand and follows the making of a microprocessor. The notes identify mostly visual communication with little narration. A continuous account of production keeps separate facts about materials and processing connected. This example puts the manufacturing journey at the centre instead of asking a general audience to start with a detailed specification.
Intel follows microprocessor production from sand in a 2:10 video with little narration. It introduces chip manufacturing to people who recognize the finished technology but may not know its origins. The example shows how a material-to-product sequence can carry a technical subject with limited spoken copy.
A business team considering cloud services first needs to understand what it is buying. Owning data-centre capacity and accessing resources on demand involve different models. Product comparison is difficult while that distinction remains unclear.
AWS defines the category and connects it with tasks such as backup and development. If the category is not grounded first, prices and capabilities arrive before the buyer understands the service model. This differs from Fujitsu’s application-level story. AWS is establishing the broader model within which later product decisions can take place.
AWS defines cloud computing as on-demand IT resources with pay-as-you-go pricing instead of owning data centres. It covers uses including backup, disaster recovery, development and analytics. Technology teams can take a lesson from giving the service model a definition before moving into applications.
People use search without seeing the stages behind a results page. A public-facing account needs to connect that familiar action with the system’s work. It does not need to begin at the level required to build or operate the system.
Google Search Central organizes the topic into crawling, indexing and serving. The sequence keeps different search concepts from looking like unrelated activities. A short introduction to the stages also gives a longer educational series a shared starting point. The public question is how search works, not how to configure a product.
Gary Illyes introduces the three stages of Search: crawling, indexing and serving. The video also opens a wider series for people learning how Search works. A technology organization can use a small set of stages to make a large system approachable before expanding into deeper lessons.
A developer familiar with a Node.js server is assessing another way to run an application. A broad promise about a platform is not enough. They need to connect the new environment with work they already know.
Cloudflare compares the traditional server with Workers and then converts an Express app. Without that bridge, a developer may understand the platform’s vocabulary without knowing how it affects an existing application. The sequence moves from architectural differences into a concrete migration task. That is a more specialized starting point than the public and category introductions above.
Cloudflare compares a traditional Node.js server with Workers through isolates, the global edge network and cold starts. It then converts an Express app into a Worker. For developer content, the lesson is to connect architectural differences with a familiar application rather than stop at terminology.
Introduce architecture one relationship at a time. First identify the input and the practical output. Then add the components the technology buyer needs to understand that transformation. A diagram that labels everything at once asks the audience to find the story themselves.
Fujitsu’s message offers a practical order: hospital data, scheduling constraints and proposed changes. I preserve that decision path in the script before adding a deeper technical view for specialist audiences.
Choose consistent labels for the same component throughout the video. Renaming an element halfway through may look like introducing a new part of the system. Use motion to show a meaningful change instead of keeping every element active. The audience needs to know where to look and why.
A practical review can start with a still version of the diagram. Ask whether the core relationship is understandable without narration. Then check whether the narration adds the necessary context. If both channels are overloaded, simplify the sequence before spending more time on the finished graphics.
A metaphor should make one relationship easier to understand. It should not quietly change what the technology can do. Name the limit of the comparison when that limit matters.
For a technical review I ask an engineer which parts of the visual video are literal and which are illustrative. Then I test it with someone outside the team. The video needs to remain understandable without implying capabilities that the product does not have.
Keep the metaphor close to the actual decision. A comparison that describes the purpose of a system may be practical in the opening and unnecessary in the detailed section. There is no need to stretch it across every feature.
For an AI-related product, check whether the visual implies intention or certainty beyond the video. A recommendation should remain recognizable as a recommendation. The technology buyer should understand the role of the output and the person using it. That distinction is especially practical when the system helps people assess alternatives rather than taking responsibility for the whole decision.
Write the technical question before selecting components. For a system buyer it may concern a decision such as scheduling. For a beginner it may concern the difference between quantum and traditional computing.
Check the baseline knowledge separately for executives and developers. Cloudflare can begin from Node.js and Express. A public account of search needs a starting point that does not assume software implementation experience.
Map inputs, constraints and outputs in the script. Fujitsu’s scheduling account provides that structure. For a development tutorial, add the transition from a known application to the new environment instead of stopping at architecture.
Related reading: explainer videos guide.
Use one naming system across diagrams and narration. Distinguish a literal component from a metaphor so a technical reviewer can check both the system’s accuracy and the meaning a non-specialist may take from it.
Related reading: explainer video cost.
Keep category lessons separate from version-sensitive implementation guides. An introduction to cloud computing and a tutorial converting an application have different update triggers and should not depend on the same maintenance schedule.
Match the detail to the technology buyer’s task. A developer deciding how to use a platform needs different information from a leader assessing a solution. Define unfamiliar terms at the point they become necessary and remove detail that does not support the intended decision.
Use 3D when spatial relationships or internal geometry are central to understanding. A 2D video may be enough for a workflow, signal path or broad concept. Choose according to the information the buyer needs rather than the perceived prestige of the format.
Describe the input, the task and the practical output. State the role of the human user and any important limits. Avoid treating the label AI as the video itself. Fujitsu’s message connects its system to a specific scheduling decision.
Include a claim only when the organization can support its wording and scope. Identify the relevant conditions. A result from one trial should not become an unconditional promise about every deployment.
A product or concept introduction often works in one to three minutes. Developer and technical content can run longer because the viewer is learning to use something.
Focus on the problem and the decision the product supports, since those change less than the interface. Avoid screens that will be out of date at launch.
Include them for technical audiences who will use them. For business audiences, show the decision or outcome and keep the architecture simple.
They use them on product pages, in documentation, at events and in sales meetings. Developer videos often sit inside docs, next to the task they explain.
Start with the question the technology helps someone answer. The architecture becomes easier to follow when the technology buyer understands why its parts matter.
Larry is the founder and Chief Storyteller at Creamy Animation, founded in 2009. He leads a team that creates story-driven videos for businesses and nonprofits. 15+ years in video strategy and production, specializing in SaaS, B2B, and nonprofit storytelling. A marketer, designer, and animator, Larry has overseen the production of more than 1,500 videos for Fujitsu, Logitech, Warner Brothers, NFL, Blockdaemon, Astronomer, Canonical, and 370+ others.
For Larry, God is first, and everything else is a blessing that comes from serving Him. When he’s not working, he’s hanging out with his wife and three kids, playing the piano, or pursuing his filmmaking side hustle.
