Seeq built a live KPI dashboard for a pharma continuous manufacturing line.
The company struggled to aggregate data across assets and spot drift before variables left range. It deployed Seeq with OSIsoft PI and Amazon Redshift, including data cleansing, custom deviation and idle-time calculations and a dashboard in Seeq Organizer. The page states 30 minutes per day per engineer saved on data aggregation.
Seeq is an industrial analytics software vendor used by pharma and biotech engineers for batch analysis, deviation investigation and scale-up
This sits in the Ship stage of the AI use-case lifecycle: Named examples from the vendors pharma teams use to get an AI system live inside a real, regulated production workflow — validation, CRM, safety and clinical systems of record.
Published by Seeq on its own site — read the original case study on seeq.com ↗
Related use cases
- 01Eli Lilly used PI Event Frames and Seeq Vantage AI for faster deviation investigations and monitoring.
- 02Sanofi used Seeq to reconstruct a loss-of-sterility incident in aseptic processing.
- 03Regeneron embedded Seeq in tech transfer and cut alert noise from 700 per batch to about 40 per month.
- 04A biopharma used Seeq on AWS to predict bad fill-weight batches before completion.
- 05Seeq let a biologics team compare lab and pilot batches without spreadsheets, speeding scale-up.
- 06Merck uses OSIsoft and Seeq analytics on AWS to support continuous drug manufacturing.