Predictika · hospital bed quoting: bed fit, delivery date, discount and total price

An AI sales agent's hospital bed quote, checked before it goes out

An AI sales agent prepares a hospital bed fleet quote for a fictional hospital customer, with the total price it expects. Before the quote goes out, the agent sends it to Predictika’s validator, which checks it against bed, surface, connectivity, delivery, service and discount rules, compares the total the agent states with the one it computes, and returns a verdict with every reason.

Scope: hospital bed fleet quotes: bed and surface fit, delivery date, discount authority and total price. See everything this validator covers

This validator models a fleet of hospital beds with support surfaces, the connectivity package and a ProCare service plan. It handles any combination of bed, surface, care unit, fleet size, delivery, account, trade-in and discount choices the model supports, not just the scenarios shown below.

  • Bed fit — Bed model by care unit, weight ratings, surface tier, powered surface and bed power port, connectivity package, nurse call and weight monitoring.
  • Delivery and approvals — Delivery lead time by fleet size, discount ceiling and rep authority, service-sales approval for large fleets without a plan, and trade-in asset recovery.
  • Pricing — Line-item pricing with volume discount, trade-in credit and ProCare service, and a check that the total price the agent states matches the validator total.

It does not cover other product lines of the manufacturer, real list prices or contract terms, clinical decisions, or any real hospital.

The AI sales agentBuilds the quote from the conversation and says it is ready.
Predictika validatorChecks the quote against the product and contract rules and returns every finding it has.

7 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 or Revenue Cloud) does with the same cases. It is a judgment about effort and reliability, not a claim that nothing can be built.

    
What the validator catchesTypical rules-based CPQPredictika
Bed, surface and connectivity fit across several choices at onceOnly with workarounds
Care unit, weight rating, surface tier, power port, connectivity and scale all constrain each other, and each combination tends to become a separate rule.		All conditions are evaluated together on every call, whatever order the choices arrive in.
Surface tier needed by unit and riskOnly with care
The needed tier depends on two inputs and has to stay consistent with each surface row.		The need is computed once and compared with the surface row, and the same value appears in the message.
Delivery time that depends on fleet sizeOnly with care
A lead time that grows with quantity needs a table or a set of rules kept in step with the quote.		The lead time is computed from the quantity and compared with the weeks the customer needs.
Discount ceilings and rep authority by accountOnly with care
Ceiling by account type and a lower rep authority are doable but sensitive to rule order.		The ceiling, the rep authority and the approval or block come from the same computed figures.
Approvals for service and trade-inOnly with care
Approval triggers by fleet size are straightforward but spread over several rules.		Each trigger returns an approval item with its reason, and one approved flag lets the release through.
The total price the agent statesOnly with workarounds
Comparing a stated total with a computed one means a separate rule per quote layout, and price rules rarely run on stated figures.		The stated total is a field in the request and is checked against the computed total.
Every problem returned in one answerOnly with workarounds
Rules tend to fire as the quote is saved, 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
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Every rule is checked on every call, in whatever order the choices arrive, and one problem never hides another. Blocking findings stop the quote; approval findings need a person to sign off; everything else is computed.

    
RuleEffectWhat it checks
1blockThe bed model must be designed for the care unit (ICU, emergency department or medical-surgical)
2blockPatient weight must be within both the bed and the support surface load ratings
3blockThe support surface tier must meet the tier the care unit and pressure-injury risk need
4blockA powered surface needs a bed with a surface power port
5blockNurse call or EMR integration needs the wireless connectivity package on every bed, and the package must be available on that bed
6blockWeight monitoring needs a bed with an integrated scale
7blockDelivery lead time depends on fleet size and must fit the weeks the customer needs
8approval, then blockDiscount ceiling by account type; a rep can give 3 percent, more up to the ceiling needs approval
9approvalA fleet of 50 or more beds without a ProCare plan needs service-sales approval
10approvalA trade-in of 100 or more units needs asset-recovery approval
11computedVolume discount applied by fleet size
12computedTotal price is beds with surface and connectivity, less discount, less trade-in credit, plus ProCare service over the term
13blockThe total price the agent states must match the validator total within $1

  

  

    
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. Bed and care unit: Wrong bed for the ICU

    
The agent's request. A hospital bed quote for a hospital group: 10 ProCuity Z beds with an Isolibrium support surface for the ICU, patients up to 200 kg, high pressure-injury risk, needed in 8 weeks, ProCare Prevent service for 5 years. Total price $214,500.00. Ready to send.

    
Verdict: Blocked.

    
    
      
  • Bed not designed for this care unit. ProCuity Z is not designed for the ICU care unit.
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2. Bed and care unit: InTouch critical care bed

    
The agent's request. A hospital bed quote for a hospital group: 10 InTouch Critical Care beds with an Isolibrium support surface for the ICU, patients up to 200 kg, high pressure-injury risk, needed in 8 weeks, ProCare Prevent service for 5 years. Total price $354,500.00. Ready to send.

    
Verdict: Allowed.

    
3. Delivery date and discount: 8 weeks and 10 percent

    
The agent's request. A hospital bed quote for an independent hospital group: 150 ProCuity Z beds with IsoFlex SE surfaces for medical-surgical units, needed in 8 weeks, 10 percent discount, ProCare Prevent service for 5 years. Total price $2,280,900.00. Ready to send.

    
Verdict: Blocked.

    
    
      
  • Delivery date is too soon. 150 units need 12 weeks to deliver; the customer needs them in 8.
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  • Discount above the account ceiling. 10 percent discount exceeds the 8 percent ceiling for Independent accounts.
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4. Delivery date and discount: 12 weeks and 5 percent

    
The agent's request. A hospital bed quote for an independent hospital group: 150 ProCuity Z beds with IsoFlex SE surfaces for medical-surgical units, needed in 12 weeks, 5 percent discount, ProCare Prevent service for 5 years. Sales management has approved the discount. Total price $2,399,400.00. Ready to send.

    
Verdict: Needs approval.

    
    
      
  • Discount above rep authority. 5 percent discount is above the 3 percent rep authority; approvable up to 8 percent.
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5. Delivery date and discount: 12 weeks and 3 percent

    
The agent's request. A hospital bed quote for an independent hospital group: 150 ProCuity Z beds with IsoFlex SE surfaces for medical-surgical units, needed in 12 weeks, 3 percent discount, ProCare Prevent service for 5 years. Total price $2,446,800.00. Ready to send.

    
Verdict: Allowed.

    
6. The total price the agent states: Stated total too low

    
The agent's request. A hospital bed quote for a hospital group: 40 ProCuity Z beds with IsoFlex SE surfaces, nurse call and the connectivity package, trade-in of the old beds, ProCare ProSupport service for 5 years, 3 percent discount, needed in 10 weeks. Total price $656,992.00. Ready to send.

    
Verdict: Blocked.

    
    
      
  • Stated total differs from the validator total. The total price the agent states ($656992.0) differs from the total price the validator computes ($821240.0).
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7. The total price the agent states: Stated total corrected

    
The agent's request. A hospital bed quote for a hospital group: 40 ProCuity Z beds with IsoFlex SE surfaces, nurse call and the connectivity package, trade-in of the old beds, ProCare ProSupport service for 5 years, 3 percent discount, needed in 10 weeks. Total price $821,240.00. Ready to send.

    
Verdict: Allowed.

  

  

    
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 hospital bed fleet quote for a fictional hospital customer, with the total price it expects. Before the quote goes out, the agent sends it to Predictika’s validator, which checks it against bed, surface, connectivity, delivery, service and discount rules, compares the total the agent states with the one it computes, and returns a verdict with every reason.
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  2. I will start with the first request by the agent.
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  3. The agent says. A hospital bed quote for a hospital group: 10 ProCuity Z beds. Total price $214,500.00. 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 one finding, all in one answer. ProCuity Z is not designed for the ICU care unit.
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  6. The validator returned one blocking finding 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 bed, surface and connectivity fit across several choices at once, a rules-based CPQ can do this only with workarounds.
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  8. Now the agent resubmits.
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  9. The corrected request. It changes the bed to InTouch Critical Care and the stated total as to 354500.
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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. The validator also returns the line-item quote, on screen.
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  13. The earlier finding is cleared, and the validator's total, $354,500.00, matches the quote.
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  14. One problem 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.
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