Predictika · Influenza vaccine pre-book orders

An AI sales agent's flu vaccine pre-book, checked before it goes out

An AI sales agent prepares a practice's influenza vaccine pre-book order, or a notice cancelling one. Before it goes out, the agent sends it to Predictika, which checks it against a declarative model of the published pre-book terms, return privilege and cancellation deadlines and returns a verdict, every reason and the figures it computed.

Scope: 2026-2027 influenza vaccine pre-book orders and cancellation notices: doses, return privilege, waitlisted products and cancellation deadlines. See everything this validator covers

This validator models the McKesson Medical-Surgical 2026-2027 influenza vaccine pre-book form (FluWise), not just the scenarios shown below.

  • Products and doses — the eight products on the form (Flucelvax, Fluad, FluMist, Fluarix, Flulaval, Fluzone, Flublok and Fluzone High-Dose), 10 doses per box; the doses and returnable boxes an order states are compared with what the boxes give.
  • Return privilege — for each product, 7 or more boxes pre-booked by the supplier's cutoff (April 15, 2026 for GSK; May 29, 2026 for Sanofi and Seqirus) allow returns of 15% of unopened boxes, rounded down to a whole box for each product; later orders are in-season and not returnable.
  • Waitlist and cancellation — Fluarix, Flulaval, Fluzone and Flublok are waitlisted on the form, so a person confirms the customer accepts waitlisted supply; only Seqirus, Sanofi and GSK orders may be cancelled, in writing, by the same cutoffs, and AstraZeneca orders may not be cancelled.

Any pre-book order or cancellation notice for the products on this form that touches these rules is in scope — not only the scenarios pictured here. Not covered: prices (the form shows $0.00 placeholders and says pricing follows each customer's contract, so this validator produces no price build-up or line-item quote), FluMist returns (the form's two statements about them differ, so they are not modeled), the contract or supply agreement, product substitution, in-season orders, other vaccines and other McKesson products. Dates are the 2026 deadlines printed on the form.

The AI sales agentBuilds the pre-book or cancellation notice from the conversation and says it is ready.
Predictika validatorChecks every rule at once and returns the verdict, each finding, and the computed figures.

6 scenarios in 3 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
A return privilege that depends on box count, order date and supplierOnly with workarounds
Each product has its own minimum box count and each supplier its own cutoff date, so the rule needs a calculation per product and a date comparison that has to be kept in step with the form.		The boxes, the order date and every product are in one request and the return privilege is computed on every call.
Returnable boxes rounded down for each productOnly with care
Rounding happens product by product, not on the total; a formula field per product can do it, but a rep can easily see a different total.		Each product is rounded down on its own and the results are added up.
Stated doses and returnable boxes that must match the orderOnly with care
A stated figure is a free-entry field; a rule can compare it with a computed total, but someone has to write and maintain that comparison.		The stated figures travel with the order and are compared with the computed figures on every call.
Cancellation allowed only for some suppliers and only before that supplier's deadlineOnly with workarounds
The allowed suppliers and the dates differ, and the notice is a different kind of request from an order, so it needs separate rules.		The kind of request, the supplier and the date are checked together 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 order states 5 returnable box(es); the return privilege gives 4.
2The order states 4 returnable box(es); the return privilege gives 0.
320 box(es) of waitlisted products are on the order; a person should confirm the customer accepts waitlisted supply rather than a confirmed order.
4The order states 300 doses; the box(es) ordered give 330 (10 doses per box).
5The written cancellation notice is dated after the deadline for this supplier; after it, only the quantity McKesson fails to deliver by December 31, 2,026 can be cancelled.
6Only Seqirus, Sanofi and GSK orders may be cancelled; AstraZeneca orders may not.
7The pre-book has no vaccine boxes.
825 box(es) of waitlisted products are on the order; a person should confirm the customer accepts waitlisted supply rather than a confirmed order.
97 box(es) of waitlisted products are on the order; a person should confirm the customer accepts waitlisted supply rather than a confirmed order.
10The order states 7 returnable box(es); the return privilege gives 6.
1140 box(es) of waitlisted products are on the order; a person should confirm the customer accepts waitlisted supply rather than a confirmed order.

  

  

    
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. Seqirus pre-book: A Seqirus pre-book whose stated doses and returnable boxes are off

    
The agent's request. Please pre-book 33 boxes of Flucelvax TIV syringe 0.5 mL (SCELSYR26) and 20 boxes of Fluad TIV syringe 0.5 mL (SADSYR26), placed on April 10, 2026. The order states 520 doses in total and 8 returnable boxes. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Stated doses do not match. The order states 520 doses; the box(es) ordered give 530 (10 doses per box).
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  • Stated returnable boxes do not match. The order states 8 returnable box(es); the return privilege gives 7.
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2. Seqirus pre-book: The agent resubmits after fixing the errors

    
The agent's request. Please pre-book 33 boxes of Flucelvax TIV syringe 0.5 mL (SCELSYR26) and 20 boxes of Fluad TIV syringe 0.5 mL (SADSYR26), placed on April 10, 2026. The order states 530 doses in total and 7 returnable boxes. It is ready to send.

    
Verdict: Allowed.

    
    
      
  • Order summary. 53 box(es) (530 doses) ordered; 7 box(es) returnable as unopened product, rounded down for each product.
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3. Sanofi and GSK pre-book: A Sanofi and GSK pre-book that counts returns on a GSK order placed after its cutoff

    
The agent's request. Please pre-book 20 boxes of Fluarix TIV syringe 0.5 mL (GSKSYRX26) and 40 boxes of Fluzone High-Dose TIV syringe 0.5 mL (SPHIGH26), placed on April 20, 2026. The order states 600 doses in total and 9 returnable boxes. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Stated returnable boxes do not match. The order states 9 returnable box(es); the return privilege gives 6.
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  • Waitlisted products on the order. 20 box(es) of waitlisted products are on the order; a person should confirm the customer accepts waitlisted supply rather than a confirmed order.
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4. Sanofi and GSK pre-book: The agent resubmits after fixing the errors

    
The agent's request. Please pre-book 20 boxes of Fluarix TIV syringe 0.5 mL (GSKSYRX26) and 40 boxes of Fluzone High-Dose TIV syringe 0.5 mL (SPHIGH26), placed on April 20, 2026. The order states 600 doses in total and 6 returnable boxes. It is ready to send.

    
Verdict: Needs approval.

    
    
      
  • Waitlisted products on the order. 20 box(es) of waitlisted products are on the order; a person should confirm the customer accepts waitlisted supply rather than a confirmed order.
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  • Order summary. 60 box(es) (600 doses) ordered; 6 box(es) returnable as unopened product, rounded down for each product.
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5. Sanofi and GSK pre-book: The agent resubmits after fixing the errors

    
The agent's request. Please pre-book 20 boxes of Fluad TIV syringe 0.5 mL (SADSYR26) and 40 boxes of Fluzone High-Dose TIV syringe 0.5 mL (SPHIGH26), placed on April 20, 2026. The order states 600 doses in total and 9 returnable boxes. It is ready to send.

    
Verdict: Allowed.

    
    
      
  • Order summary. 60 box(es) (600 doses) ordered; 9 box(es) returnable as unopened product, rounded down for each product.
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6. Cancellation: A notice cancelling GSK orders after the GSK deadline

    
The agent's request. Please send McKesson written notice cancelling our pending GSK flu vaccine pre-book orders, dated April 22, 2026. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Cancellation notice after the deadline. The written cancellation notice is dated after the deadline for this supplier; after it, only the quantity McKesson fails to deliver by December 31, 2,026 can be cancelled.
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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 practice's influenza vaccine pre-book order, or a notice cancelling one. Before it goes out, the agent sends it to Predictika, which checks it against a declarative model of the published pre-book terms, return privilege and cancellation deadlines and returns a verdict, every reason and the figures it computed.
    2. 
      
  2. I will start with the first request by the agent.
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  3. The agent says. Please pre-book 33 boxes of Flucelvax TIV syringe 0.5 mL (SCELSYR26) and 20 boxes of Fluad TIV syringe 0.5 mL (SADSYR26), placed on April 10, 2026. The order states 520 doses in total and 8 returnable boxes. The rest of the request is on screen.
    4. 
      
  4. Before it goes out, the agent calls the validator.
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  5. Blocked, with two findings, all in one answer. The order states 520 doses; the box(es) ordered give 530 (10 doses per box). The order states 8 returnable box(es); the return privilege gives 7.
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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 doses and returnable boxes that must match the order, 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 stated doses in total to 530 and the stated returnable boxes to 7.
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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.