Lunavi built a system that writes employee biographies for you. It keeps writing them as your roster changes, and it leaves the final say with a human.

It starts from data you already have. The stats, credentials, roles, and results sitting in your systems become the raw material. From there it runs a simple loop.
The output reads like something a person wrote, the kind of profile that makes a reader stay. That is the difference between content people skim past and content that builds trust.
Nothing publishes unsupervised. Every draft lands in a review step where your team can approve it, edit it, or ask for another version. Automation speed, human judgment.
Whether you have fifty people or five thousand, the effort to keep them all current stays flat. The system does the drafting. Your team does the deciding.
When the underlying data changes, profiles refresh. No annual scramble. No backlog quietly rotting in the background.
Under the hood it runs on Microsoft Azure and Azure OpenAI Service, with the data pipeline built to pull from the systems you already use and feed cleaner data forward into whatever you build next.
PRCA went from about 25 athlete biographies per event to more than 600, refreshed automatically every week. Every contestant's story gets told, not just the winners'. Same system, same loop you can run yourself.
Read the PRCA case studyPick a context, see the structured data the system would ingest, generate a draft, then approve, edit, or regenerate. Approve it and it publishes as a finished profile, headshot and all.
What's missing is the time, and that's the part this solves.
See what this could do for your team