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AI agent for microbiologists

Fermentation Batch Monitoring Agent

Batch problems caught early enough to act

MonitoringRisk managementAnalysisScience and research
See how it worksGet access
Fermentation Batch Monitoring Agent: what goes in, what the agent does and what you get

What it does

Fermentation batches run for days, and problems caught early save the batch. This agent watches live data for pH, dissolved oxygen, temperature and off-gas, plus regular samples, and compares each batch with the golden batch profile. It flags early signs of trouble, such as slow growth, changes in oxygen uptake, foaming or pH drift. Before raising an alarm, it checks the sensor readings against the latest offline samples. If the samples do not confirm the deviation, it flags a possible sensor fault instead. For real deviations, it suggests actions from your playbook and drafts a deviation record. You approve any process action and any decision to end a batch early. Edge case: a sudden drop in dissolved oxygen with rising off-gas carbon dioxide is flagged as possible contamination.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedNo 1 STARTS WHEN Batch starts 2 USES A TOOL Stream sensor and sample data 3 DOES Compare with the golden batch profile 4 CHECKS THE RESULT Do offline samples confirm the deviation? If not: flag a possible sensor fault. Back to step 2. 5 DOES Suggest actions from the playbook 6 YOU APPROVE Scientist approves actions 7 RESULT Batch report
Read the steps as a list
  1. Batch starts
  2. Stream sensor and sample data
  3. Compare with the golden batch profile
  4. Do offline samples confirm the deviation?If not: flag a possible sensor fault. Back to step 2.
  5. Suggest actions from the playbook
  6. Scientist approves actionsThe agent waits here for your OK.
  7. Batch report

How it decides

It flags deviations from the golden profile beyond set bands confirmed by offline samples.

  • Confirm with offline samples
  • Flag contamination patterns
  • Use playbook actions only

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Deviation bands
  • Golden batch
  • Playbook
  • Alert channel

What keeps you in control

It always asks you first

  • Process actions
  • Ending a batch early

Hard limits

  • Never changes setpoints

It stops when

  • Done: batch report filed
  • Stop: data feed lost

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensAt hour 31 of batch F-118, dissolved oxygen read 12% higher than the golden profile and pH had drifted 0.15 low. The agent checked the 30-hour offline sample before flagging. Cell density was normal, so it went back and compared the DO probe with the backup probe, which read in line with the profile. It logged a probe fault, not a process issue. The scientist approved a probe swap at the next sample.

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