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Hi @Khaja_Zaffer ,

Great question  and happy belated Halloween 🎃

From what we’re seeing across clients in healthcare and life sciences, Generative AI has absolutely moved beyond the buzzword stage. It’s now being operationalised, but selectively, in areas where governance, accuracy, and patient privacy can be controlled.

Some examples we’re actively working on at Unifeye include:

• Ambient CIinicaI Documentation, exactly as you mentioned  where large language models summarise consultations into structured EHR entries.

• GenAI for biomedical literature review and pharmacovigilance, to accelerate dr-ug discovery and evidence synthesis.

• Patient engagement and triage assistants, securely connected to de-identified data via Unity Catalog and Mosaic AI.

The real shift is that healthcare organisations now combine trusted data foundations (like Delta + Unity Catalog) with domain-specific fine-tuning, ensuring explainability, compliance, and auditability. That’s where the jobs are growing: not just “prompt engineers”, but data engineers, ML engineers, and AI architects who can productionise GenAI responsibly.

So yes, the momentum is real, and it’s only accelerating.

Hello @bianca_unifeye 

Thank you so much. thats what I was looking for. 

Do you have any idea what tech stack if you hiring in gen ai related roles? 

How much python do you expect, what in Python do you expect.