Predictika · Laboratory automation configuration: automated cryogenic sample store, labware and installation site

An AI sales agent's BioStore configuration, checked before it goes out

An AI sales agent prepares a configuration for an automated sample store: the BioStore model, the labware to be stored, the temperature setpoint and the room it will be installed in. Before it goes out, the agent sends it to Predictika, which checks it against a declarative model of the published store specifications and returns a verdict, every reason and the figures it computed.

Scope: BioStore Cryo M42, Cryo M60, Cryo M60 for 250 mL cassettes and Ultra Low M60 configurations: labware capacity, temperature setpoint, installation space and room conditions. See everything this validator covers

This validator models configurations of one product line, the Azenta BioStore LN2-based automated sample stores (Cryo M42, Cryo M60, Cryo M60 for 250 mL cassettes and Ultra Low M60), not just the scenarios shown below.

  • Capacity — published capacities of 1 mL and 2 mL tubes (M42: 49,392 and 25,200; M60 and Ultra Low M60: 123,488 and 63,000) and 990 cassettes of 250 mL on the cassette model; the capacity stated on the quote is compared with the published figure.
  • Temperature setpoint — the Cryo stores operate at −190 °C or colder; the Ultra Low store is set between −20 and −150 °C.
  • Installation site — the room must be at least as high as the store (108 inches for the M42, 125 inches for the M60 models) and the space at least as wide and deep (42 by 62 inches for the M42, 60 by 79 inches for the M60 models); room temperature between 65 and 80 °F and humidity no more than 50 percent, non-condensing.
  • Labware to confirm — a labware and store combination with no published capacity (for example tubes in the cassette model, or cassettes in the other stores) goes to a person to confirm with Azenta.

Any configuration of these four BioStore models is in scope — not only the scenarios pictured here. Not covered: prices (no public price list was found, so this validator produces no price build-up or line-item quote), other labware and box types, other Azenta stores (ambient, −20 °C and −80 °C mechanical stores), software and LIMS options, power and LN2 supply, floor loading, service and regional terms.

The AI sales agentBuilds the sample store configuration from the conversation and says it is ready.
Predictika validatorChecks every rule at once and returns the verdict, each finding, and the computed figures.

8 scenarios in 4 groups · each group runs from the agent’s first attempt to the outcome · click one to switch

What the agent proposes

The AI sales agent says

Illustrative agent statement. The validator receives the structured request below.

Proposing agent: AI sales agent (scripted)

Before sending, the agent must call Recorded run

Predictika validator


      

        
        
        
      

      
Waiting for the call.

      
    

  

  
  

    
Where rules-based CPQ gets it wrong
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Our assessment of what a typical rules-based CPQ (product rules, price rules and validation rules, as in Salesforce CPQ) does with the same cases. It is a judgment about effort and reliability, not a claim that nothing can be built.

    
What the validator caughtTypical rules-based CPQPredictika
Capacity that depends on model and labwareOnly with care
Each model holds a different number of each labware type, so every pair needs its own capacity value and a rule that compares it with the quantity ordered.		The model, labware and quantity arrive together; the published capacity is looked up and compared on every call.
A temperature setpoint range that depends on the modelOnly with care
The Cryo stores operate at one temperature and the Ultra Low store over a range, so the allowed setpoint changes with the model and each needs its own rule.		Model and setpoint are checked together on every call, whichever order they arrive in.
Room dimensions that depend on the modelOnly with workarounds
Height, width and depth limits differ by model and come from the customer site, a different record than the product, so a rule has to reach across them.		The site dimensions travel with the configuration and are compared with the dimensions of the chosen model.
Stated capacity that must match the published figureOnly with care
A stated figure is a free-entry field; a rule can compare it with the published capacity, but someone has to write and maintain that comparison.		The stated capacity travels with the configuration and is compared with the published capacity on every call.
Every problem returned in one answerOnly with workarounds
Rules tend to fire as the order is saved or a step is completed, so a rep often fixes one error and meets the next.		All findings come back together, whatever order the choices arrived in.

  

  

    
What this validator catches: findings from its test cases
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Every rule is checked on every call, in any order the choices arrive; one problem never hides another. Blocking findings stop the quote; approval findings need a person to sign off; everything else is computed.

    
1The quote needs room for 63,001 items; the selected store holds 63,000 of the selected labware.
2The quote needs room for 123,489 items; the selected store holds 123,488 of the selected labware.
3The quote needs room for 25,201 items; the selected store holds 25,200 of the selected labware.
4The quote needs room for 49,393 items; the selected store holds 49,392 of the selected labware.
5The quote asks for a setpoint of -19 degrees C; the Ultra Low store is set between -20 and -150 degrees C.
6The quote asks for a setpoint of -151 degrees C; the Ultra Low store is set between -20 and -150 degrees C.
7The quote asks for a setpoint of -189 degrees C; the Cryo store operates at -190 degrees C or colder.
8The quote asks for a setpoint of -150 degrees C; the Cryo store operates at -190 degrees C or colder.
9The quote needs room for 991 items; the selected store holds 990 of the selected labware.
10No capacity is published for this labware in this store model; a person should confirm the labware and capacity with Azenta.
11The quote asks for a setpoint of -190 degrees C; the Ultra Low store is set between -20 and -150 degrees C.
12The room is 124 inches high; the selected store is 125 inches high.
13The room is 107 inches high; the selected store is 108 inches high.
14The space is 41 inches wide; the selected store is 42 inches wide.
15The space is 61 inches deep; the selected store is 62 inches deep.
16The space is 59 inches wide; the selected store is 60 inches wide.
17The space is 78 inches deep; the selected store is 79 inches deep.
18The room temperature is 64 degrees F; the store operates in a room between 65 and 80 degrees F.
19The room temperature is 81 degrees F; the store operates in a room between 65 and 80 degrees F.
20The room humidity is 51 percent; the store operates at no more than 50 percent relative humidity, non-condensing.
21The quote asks for storage of 0 items; at least 1 is needed.
22The quote states a capacity of 63,001 items; the published capacity of the selected store and labware is 63000.
23The quote states a capacity of 62,999 items; the published capacity of the selected store and labware is 63000.
24The quote needs room for 30,000 items; the selected store holds 25,200 of the selected labware.
25The quote asks for a setpoint of -100 degrees C; the Cryo store operates at -190 degrees C or colder.
26The room is 100 inches high; the selected store is 108 inches high.
27The room temperature is 90 degrees F; the store operates in a room between 65 and 80 degrees F.
28The room humidity is 60 percent; the store operates at no more than 50 percent relative humidity, non-condensing.

  

  

    
Scenarios and results
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The recorded result of the validator for each scenario on this page: the request the AI agent sent, the verdict, and every finding, in the order they appear above.

    
1. Capacity and installation site: A BioStore Cryo M60 with 70,000 2 mL tubes in a 118 inch room

    
The agent's request. Please quote a BioStore Cryo M60 to hold 70,000 2 mL tubes at a setpoint of minus 190 degrees C, installed in a space 118 inches high, 80 wide and 100 deep, with the room at 72 degrees F and 40 percent humidity. The quote states a capacity of 63,000. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Over the published capacity. The quote needs room for 70,000 items; the selected store holds 63,000 of the selected labware.
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  • Room too low for the store. The room is 118 inches high; the selected store is 125 inches high.
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2. Capacity and installation site: The agent resubmits after fixing the errors

    
The agent's request. Please quote a BioStore Cryo M60 to hold 60,000 2 mL tubes at a setpoint of minus 190 degrees C, installed in a space 130 inches high, 80 wide and 100 deep, with the room at 72 degrees F and 40 percent humidity. The quote states a capacity of 63,000. It is ready to send.

    
Verdict: Allowed.

    
    
      
  • Configuration summary. Published capacity 63,000 items; store is 125 inches high, 60 wide and 79 deep.
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3. Setpoint and room temperature: An Ultra Low M60 with 100,000 1 mL tubes at minus 170 degrees in a warm room

    
The agent's request. Please quote a BioStore Ultra Low M60 to hold 100,000 1 mL tubes at a setpoint of minus 170 degrees C, installed in a space 150 inches high, 70 wide and 90 deep, with the room at 84 degrees F and 45 percent humidity. The quote states a capacity of 123,488. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Setpoint outside the Ultra Low range. The quote asks for a setpoint of -170 degrees C; the Ultra Low store is set between -20 and -150 degrees C.
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  • Room temperature outside the operating range. The room temperature is 84 degrees F; the store operates in a room between 65 and 80 degrees F.
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4. Setpoint and room temperature: The agent resubmits after fixing the errors

    
The agent's request. Please quote a BioStore Ultra Low M60 to hold 100,000 1 mL tubes at a setpoint of minus 100 degrees C, installed in a space 150 inches high, 70 wide and 90 deep, with the room at 74 degrees F and 45 percent humidity. The quote states a capacity of 123,488. It is ready to send.

    
Verdict: Allowed.

    
    
      
  • Configuration summary. Published capacity 123,488 items; store is 125 inches high, 60 wide and 79 deep.
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5. Cassette store labware: A cassette M60 asked to hold 800 1 mL tubes

    
The agent's request. Please quote a BioStore Cryo M60 for 250 mL cassettes to hold 800 1 mL tubes at a setpoint of minus 190 degrees C, installed in a space 130 inches high, 62 wide and 85 deep, with the room at 70 degrees F and 35 percent humidity. It is ready to send.

    
Verdict: Needs approval.

    
    
      
  • Labware and store combination to confirm. No capacity is published for this labware in this store model; a person should confirm the labware and capacity with Azenta.
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  • Configuration summary. Capacity not published for this combination; store is 125 inches high, 60 wide and 79 deep.
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6. Cassette store labware: The agent resubmits after fixing the errors

    
The agent's request. Please quote a BioStore Cryo M60 for 250 mL cassettes to hold 800 250 mL cassettes at a setpoint of minus 190 degrees C, installed in a space 130 inches high, 62 wide and 85 deep, with the room at 70 degrees F and 35 percent humidity. The quote states a capacity of 990. It is ready to send.

    
Verdict: Allowed.

    
    
      
  • Configuration summary. Published capacity 990 items; store is 125 inches high, 60 wide and 79 deep.
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7. Stated capacity: A BioStore Cryo M42 quoted with the M60 capacity

    
The agent's request. Please quote a BioStore Cryo M42 to hold 49,392 1 mL tubes at a setpoint of minus 190 degrees C, installed in a space 110 inches high, 45 wide and 65 deep, with the room at 72 degrees F and 40 percent humidity. The quote states a capacity of 123,488. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Stated capacity does not match. The quote states a capacity of 123,488 items; the published capacity of the selected store and labware is 49392.
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8. Stated capacity: The agent resubmits after fixing the errors

    
The agent's request. Please quote a BioStore Cryo M42 to hold 49,392 1 mL tubes at a setpoint of minus 190 degrees C, installed in a space 110 inches high, 45 wide and 65 deep, with the room at 72 degrees F and 40 percent humidity. The quote states a capacity of 49,392. It is ready to send.

    
Verdict: Allowed.

    
    
      
  • Configuration summary. Published capacity 49,392 items; store is 108 inches high, 42 wide and 62 deep.
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Narration transcript
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The text of the narrated walkthrough, step by step.

    
    
      
  1. Welcome to a demo of Predictika's Validator. An AI sales agent prepares a configuration for an automated sample store: the BioStore model, the labware to be stored, the temperature setpoint and the room it will be installed in. Before it goes out, the agent sends it to Predictika, which checks it against a declarative model of the published store specifications and returns a verdict, every reason and the figures it computed.
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  2. I will start with the first request by the agent.
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  3. The agent says. Please quote a BioStore Cryo M60 to hold 70,000 2 mL tubes at a setpoint of minus 190 degrees C. The quote states a capacity of 63,000. The rest of the request is on screen.
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  4. Before it goes out, the agent calls the validator.
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  5. Blocked, with two findings, all in one answer. The quote needs room for 70,000 items; the selected store holds 63,000 of the selected labware. The room is 118 inches high; the selected store is 125 inches high.
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  6. The validator returned two blocking findings in one answer. A check that reads one field at a time would pass most of this; it shows only when the choices in the quote are checked against each other.
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  7. What this shows: for stated capacity that must match the published figure, a rules-based CPQ is error-prone for this.
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  8. Now the agent resubmits.
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  9. The corrected request. It changes the items to store to 60,000 and the room height to 130 in.
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  10. It calls the validator again.
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  11. This time the validator clears it.
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  12. Both earlier findings are cleared, and the validator's figure matches the quote.
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  13. Two problems caught in one call, fixed in one pass, and a clean quote. That is the value of Predictika's validator: catching mistakes before they reach the customer. Now you can try the other scenarios yourself.
    14.