LLMs can generate good metadata
August 11, 2025
Not everything AI touches needs to be a reinvention. Some things just need less friction.
Most teams aren’t struggling with whether to adopt AI.
They’re struggling with where to begin that feels useful.
In our case, it didn’t start with modeling. It started with tagging.
We used LLMs to help generate metadata: across datasets, across assets. Not perfect, but faster than doing it line-by-line. It helped us shift the bottleneck.
Now we’re running small internal experiments with local LLMs--feeding them graph-aware schema and asking them to write SQL from natural language. Quiet progress. No major integrations. But enough to help someone move faster on a task they’d usually skip or delay.
These aren’t massive deployments. Just small lifts that remove mental overhead.
If there’s a lesson here, it’s this:
AI doesn’t need to replace your work. It just needs to sit in the right place—close enough to help, invisible enough to stay out of the way.
Curious what other quiet wins teams are seeing—not the demos, but what actually sticks.
#HealthcareData #DataStrategy #LLM #Enablement #Metadata #GenAI #GraphData #ClinicalAnalytics #PharmaData