Every streaming business has a set of requirements and tasks to complete in order to get to market, each with its own set of obstacles to overcome. A common challenge is the lack of manpower, teams only have so many allotted resources to utilize. That’s where leaning on AI can help.
Thankfully, Zype’s Streaming Platform has a full suite of APIs, but not every team has the resources to develop and maintain the custom code needed to run scripts. AI can be leveraged to create custom scripts that complete jobs which would have otherwise forced business users into time-consuming manual work, or required a developer to consume time generating a one-time script that may not have been worth the effort in the long run. AI can turn hours of manual work into minutes, especially when combined with APIs that enable workflow automation and video metadata scripting. Reducing manual workloads is critical.
Let’s dive into a few scenarios that have come up for several customers and how they were addressed using AI and Zype’s APIs.
In this case, AI can be used to generate a script capable of iterating through a CSV and using the Update Video API to populate all metadata fields included in the spreadsheet. As videos were uploaded and Video IDs were generated, those IDs were added to the spreadsheet to correspond with each video. Without this identifier, the script would have nothing to key off of to correctly map metadata.
The script then locates each video in the library using the Video ID and populates all metadata present in the spreadsheet. This removed a significant amount of manual data entry and allowed the team to focus on higher-value work. It also helped fast-track onboarding onto the Zype Streaming Platform, enabling the team to move more quickly into designing their apps using the Apps Creator tool.
AI Prompt: “Can you take this CSV and use the unique identifier ‘Video ID’ listed in Column A to update each corresponding video with its metadata, using Zype’s APIs? Also, please output a CSV for any Video IDs that did not get updated or if there were any errors in general.”
Zype offers the ability to add a “publish_at” date as metadata, which could be useful for this exact scenario. However, during initial creations of SOPs, the need to populate this field was not established.Going back and manually adding "publish_at" values across the entire library would be burdensome, as the "created_at" value is determined at the time the video object is created and cannot be retroactively adjusted at scale.
For most use cases, “created_at” worked as expected–only a small number of videos caused ordering issues. Rather than manually populating a new field for every video, it was far more efficient to work in the opposite direction.
Using the Update Video API, a script was generated that leveraged the View Video API to retrieve the “created_at” string from each video’s API response body and populate the “publish_at” field with the same value.
AI Prompt: “Can you take the ‘created_at’ string and use it to populate the ‘publish_at’ string with the same exact value for each individual video using Zype’s API?”
Grabbing exports from the Zype Analytics Dashboard is straightforward, as this data is readily available through the UI. The time-consuming part was the manual calculations and grouping that followed.
By leveraging the Hours Watched API in the Analytics V3 suite, a script could retrieve total stream hours for each individual video. Chaining this with the View Video API made it possible to associate each video with its corresponding Series ID and group the data accordingly.
As a part of the script, total stream hours were aggregated at the series level and royalty payouts were calculated across multiple rates.. When it came time to issue payments, the team could simply reference the master sheet, select the appropriate rate, and process payouts with confidence..
AI Prompt: “Please pull a list of all stream hours for all video titles within a certain month using Zype’s APIs, then join them by Series ID and output it in a CSV. The CSV should also calculate royalties based on stream hours; can you list a column for 10 cents, 15 cents, and 20 cents per hour streamed on each Series ID. The month should be a definable parameter when executing the script.”
In this case, we let AI do the heavy lifting by generating HTML and JavaScript. This created the boilerplate for the web developer to build upon. Using the Update Password API, the developer also needed to incorporate a password confirmation input along with validation for a strong password. With a quick prompt, AI generated the HTML that the developer could plug into the website and pass a token into the flow:
AI Prompt: “Can you use the Update Password API to generate HTML for end users to reset their password? It should have a confirm password field and require a strong password that consists of 8 characters, with uppercase and lower case letters, and uses at least 1 number and symbol.”
Google can better understand video content through a Video Sitemap, which includes MP4 assets to support SEO. In this case, a short clip was sufficient.
There was no desire to introduce additional software for clipping or storage as the goal was to keep workflows consistent within the Zype CMS. This script began by retrieving the available 720p rendition from a video object and stitching together the first 30 seconds into an MP4 using ffmpeg. It then used the Create Upload API to upload the new asset back into the Zype CMS and and associate it with the original video by assigning it as a Related Video.
As part of the process, the script reused the original video title, appending “- clip” to the end, and assigned a specific Category Value.
These clips could then be referenced in Google’s video sitemap schema to support SEO.
AI Prompt: “Can you use ffmpeg and the Zype APIs to generate a script that would take the available 720p HLS rendition and stitch together the first 30 seconds of the video to create a clip? The script should then upload the clip to Zype and associate it with the respective video as a ‘Related Video’. The script should also update metadata for the clip by recycling the same title but appending ‘- clip’ to the end of it and also assign a category value of ‘clip’ under the category title ‘type’.”
These examples represent just a small sample of how customers are accelerating workflows by pairing AI with Zype’s API ecosystem. Whether automating metadata cleanup, generating reports, calculating royalties, or building custom user experiences, AI reduces the friction of manual work and allows teams to focus more on business critical items like strategy, content, and audience growth.
Across these use cases, the common goal is to eliminate repetitive, time-consuming tasks by leveraging AI. This enables teams to innovate faster, onboard more efficiently, and deliver stronger business and user experiences.
With a full suite of APIs, Zype provides the technical foundation, while AI lowers the barrier to accessing that power. This opens the door to limitless possibilities, from operational automation to rapid prototyping, that once required dedicated engineering resources.
Explore what’s possible with Zype’s APIs and AI. Get a demo to see how modern media teams automate workflows and reduce manual work.