Predictika · Hospital beds and surfaces: care setting, patient weight, therapy and discount authority

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

An AI sales agent prepares a therapy bed and surface quote for a fictional health system. Before it goes out, the agent sends it to Predictika’s validator, which checks it against the care setting, patient weight, therapy and commercial rules, compares the total price the agent states with the one it computes, and returns a verdict with every reason.

Scope: therapy bed and surface quotes (Progressa+, Centrella Smart+, Compella and Envella beds with their surfaces), purchase or rental, with SmartCare service. See everything this validator covers

This validator models therapy bed and surface quotes in the style of Baxter (Hillrom): bed class by care setting, surface tier, safe working load, pulmonary therapy, nurse call, and purchase or rental terms. It handles any quote made of these beds, surfaces and rules, not just the scenarios shown below.

  • Beds and surfaces — Progressa+ (ICU), Centrella Smart+ (med-surg), Compella (bariatric) and Envella (air-fluidized, burn and wound), each matched to the care setting it is offered for.
  • Clinical fit — Patient weight against the safe working load of the bed and the surface, surface tier from pressure-injury risk and ICU placement, pulmonary therapy, air-fluidized pairing and nurse call connectivity.
  • Commercial terms — Purchase or rental, rental duration and fleet-size approvals, SmartCare service, discount ceilings by account type with a rep authority, and a check that the total price the agent states matches the total the validator computes.

It does not cover other Baxter product families such as infusion pumps, connected care monitoring or patient lifts, real prices or contracts, or clinical advice.

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 and surface compatibilityOnly with workarounds
Which surface goes with which bed, and which bed accepts a given therapy, usually becomes one rule per combination.
Compatibility is a property of the catalog items, checked on every call.
Care setting to bed classOnly with care
Each care setting accepts a different set of bed classes, so the setting rules multiply with the catalog.
The allowed classes are part of the model, and one rule covers every setting.
Patient weight against two ratingsOnly with care
A weight must fit both the bed rating and the surface rating, which spans several validation rules.
Both ratings are compared with the weight in one pass.
Discount ceiling by account typeOnly with care
Rep authority, account ceiling and approval route are separate rules that interact.
The ceiling and the authority are evaluated together with the requested discount.
The total 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 price 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
Bed for the care settingblockEach care setting accepts specific bed classes: ICU critical care; med-surg standard or bariatric; burn and wound air-fluidized or critical care
Patient weightblockThe heaviest patient must be within the safe working load of both the bed and the surface
Surface tierblockHigh pressure-injury risk or an ICU needs a tier 2 or higher surface
Pulmonary therapyblockCLRT and percussion/vibration therapy need a therapy-capable bed and a pulmonary surface
Air-fluidized pairingblockThe air-fluidized bed pairs only with its integrated surface
Nurse callblockNurse call integration needs a bed with connectivity
Discount ceilingblockDiscount may not exceed 12 percent for IDN accounts or 7 percent for independent accounts
Total price the agent statesblockThe total price in the request must match the total the validator computes
Long rentalneeds approvalA rental over 180 days needs finance approval
Rental fleet sizeneeds approvalRenting more than 25 units needs fleet planning approval
Discount authorityneeds approvalA discount above 4 percent, up to the ceiling, needs approval

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 for the care setting: Centrella for the ICU

The agent's request. Ten Centrella Smart+ beds with the Centrella MAX surface for the intensive care unit at Cedar Valley Health System, purchase with 5 years of SmartCare service. Total price USD 287,000. Ready to send.

Verdict: Blocked.

  • Bed for the care setting. Centrella Smart+ is not offered for the ICU care setting.

2. Bed for the care setting: Progressa+ for the ICU

The agent's request. Ten Progressa+ beds with the Progressa Pulmonary Plus surface for the intensive care unit at Cedar Valley Health System, purchase with 5 years of SmartCare service. Total price USD 714,000. Ready to send.

Verdict: Allowed.

3. The total the agent states: Stated total below computed

The agent's request. Forty Centrella Smart+ beds with the Centrella MAX surface for the medical-surgical units at Cedar Valley Health System, nurse call integration, purchase with 5 years of SmartCare service. Total price USD 1,067,640. Ready to send.

Verdict: Blocked.

  • Total price the agent stated. The stated total price of $1067640.0 does not match the $1148000.0 the validator computed.

4. The total the agent states: Stated total corrected

The agent's request. Forty Centrella Smart+ beds with the Centrella MAX surface for the medical-surgical units at Cedar Valley Health System, nurse call integration, purchase with 5 years of SmartCare service. Total price USD 1,148,000. Ready to send.

Verdict: Allowed.

5. Discount authority: 9 percent, independent account

The agent's request. Twenty Centrella Smart+ beds with the Centrella MAX surface for the medical-surgical units at Cedar Valley Health System, purchase with 5 years of SmartCare service and a 9 percent discount. Total price USD 537,100. Ready to send.

Verdict: Blocked.

  • Discount ceiling. 9 percent discount exceeds the 7 percent ceiling for Independent accounts.

6. Discount authority: 6 percent, needs approval

The agent's request. Twenty Centrella Smart+ beds with the Centrella MAX surface for the medical-surgical units at Cedar Valley Health System, purchase with 5 years of SmartCare service and a 6 percent discount. Total price USD 549,400. Ready to send.

Verdict: Needs approval.

  • Discount authority. 6 percent discount is above the 4 percent rep authority; approvable up to 7 percent.

7. Discount authority: 4 percent, within rep authority

The agent's request. Twenty Centrella Smart+ beds with the Centrella MAX surface for the medical-surgical units at Cedar Valley Health System, purchase with 5 years of SmartCare service and a 4 percent discount. Total price USD 557,600. 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 therapy bed and surface quote for a fictional health system. Before it goes out, the agent sends it to Predictika’s validator, which checks it against the care setting, patient weight, therapy and commercial rules, compares the total price the agent states with the one it computes, and returns a verdict with every reason.
  2. I will start with the first request by the agent.
  3. The agent says. Ten Centrella Smart+ beds with the Centrella MAX surface for the intensive care unit at Cedar Valley Health System, purchase with 5 years of SmartCare service. Total price USD 287,000. The rest of the request is on screen.
  4. Before it goes out, the agent calls the validator.
  5. Blocked, with one finding, all in one answer. Centrella Smart+ is not offered for the ICU care setting.
  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.
  7. What this shows: for care setting to bed class, a rules-based CPQ is error-prone for this.
  8. Now the agent resubmits.
  9. The corrected request. It changes the bed to progressa+, the surface to Progressa Pulmonary Plus and the stated net as to 714000.
  10. It calls the validator again.
  11. This time the validator clears it.
  12. The validator also returns the line-item quote. It starts with Progressa+ and Progressa Pulmonary Plus; the other line is on screen.
  13. The earlier finding is cleared, and the validator's total, USD 714,000, matches the quote.
  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. Now you can try the other scenarios yourself.