SiddhiSIDDHI LLC

AI Agents in Pharmaceutical Manufacturing

Whitepaper · Siddhi LLC

Cover of the whitepaper AI Agents in Pharmaceutical Manufacturing
For Manufacturing, Quality and IT Heads

Answers from the batch record, in plain language, on the shop floor: what the agents answer, where the model runs, how they learn without seeing your records, and why they never become part of the record.

PDF · 8 pages · free

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What you will learn

  • Why AI stalls on systems that disagree, and what one batch record changes
  • Five design rules: read-only, the person's own access, records under every answer
  • The 27 kinds of question the agents on a batch answer, with charts and quotes from your SOPs
  • Where the model runs: in the browser or on an AI box on your network; nothing sent to an AI company
  • How the agents learn from corrections without seeing your records
  • A table of each GxP risk and the control behind it

Executive summary

On a pharmaceutical shop floor, the answers people need every hour already exist in the batch record. Which batches wait for QA? Which balance is due for calibration? Is the yield trending down? Usually someone has to open several screens, binders or systems to find out.

Atto Pharma eBMR adds AI agents that answer those questions in plain language, from the plant's own records, with the records shown under every answer. Three rules make them fit for a GMP plant:

  • The record decides. An agent's answer is never part of the batch record. Agents can't record, sign or change anything.
  • The records stay in the plant. The model runs in the browser or on a computer on the plant's network, so no batch record goes to an AI company.
  • People stay in charge. When an agent isn't sure, it says how it read the question and offers the alternatives.

More from Siddhi LLC: all whitepapers · the blog · a free 14-day pilot of Atto Pharma eBMR