Predictika · Contact center editions, add-ons, named and concurrent seats, and committed usage

An AI sales agent's contact center subscription quote, checked before it goes out

An AI sales agent prepares a subscription quote for a cloud contact center platform: an edition, an optional add-on, a seat model, a number of seats, a term, a committed usage amount against expected usage, and a discount. Before the quote goes out, the agent sends it to Predictika's validator, which checks all of it together, including the net total the agent states, and reports every problem in one pass.

Scope: Subscription quotes for a Genesys Cloud style contact center platform: three editions, four add-ons, named or concurrent seats, one or three year terms and committed usage, with prices in USD. Built from general public knowledge, not from Genesys data; every price and limit is an estimate. Not affiliated with or endorsed by Genesys. See everything this validator covers

This validator checks any quote for this product line against the rules below, not just the scenarios shown on this page.

  • Editions and seat models — three editions with a minimum number of seats, named seat prices, and concurrent seat prices on the editions that offer them.
  • Add-ons — Digital Messaging, Workforce Engagement, AI Experience and Experience Analytics, the edition each needs and its own minimum number of seats.
  • Seat and term pricing — quantity price tiers and one or three year terms with a multi-year discount, built up into a seat subtotal.
  • Committed usage — an annual usage commit measured against expected usage: blocked below 50 percent, sent to the deal desk below 70 percent or above 120 percent, with a commit discount by size.
  • Discounts and the quoted total — a discount limit by order size with a rep authority of 10 percent, a director review above USD 1,000,000, and a comparison of the net total the agent states with the total the validator computes.

Any quote that touches these rules is in scope, not only the scenarios pictured here. Not checked: other Genesys products, overage billing after signing, real list prices, taxes and multi-currency quoting.

The AI sales agentBuilds the subscription quote from the conversation and says it is ready to send.
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 this 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 committed usage amount judged against expected usageOnly with workarounds
A custom ratio of two entered amounts with block and approval levels on both sides; usage terms are usually outside the product catalog.		The ratio, the review bands and the commit discount are one calculation, returned with the other findings.
An add-on that needs a higher edition and its own minimum seatsOnly with care
Product rules and quantity validation; works, but every add-on adds rules to keep in step with the editions.		The edition level and the add-on minimum are catalog attributes checked together on every call.
Named and concurrent seats with different pricesOnly with care
Price book entries or variants per seat model and a rule for the editions that do not offer concurrent seats.		The seat model selects the price column; availability is a catalog attribute.
Volume tiers combined with term and commit discountsOnly with care
Tiered price rules plus a term discount and a commit discount applied in a fixed order.		Tier, term discount and commit discount are one calculation.
A quoted total that no longer matchesOnly with workarounds
The total the agent states is a typed number; unless someone adds a recalculation rule it is accepted as is.		The validator computes the total and blocks a quote whose stated total does not match.

  

  

    
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.

    
1Fewer seats than the minimum for the edition are blocked.
2An add-on with fewer seats than its own minimum is blocked.
3An add-on that needs a higher edition than the one quoted is blocked.
4Concurrent seats on an edition that does not offer them are blocked.
5A term other than 1 or 3 years is blocked.
6A usage commit with no expected annual usage entered is blocked.
7A usage commit below 50 percent of the expected annual usage is blocked.
8A discount above the limit for the order size is blocked.
9A net total that does not match the total the validator computes is blocked.
10A usage commit below 70 percent of expected usage needs deal desk approval.
11A usage commit above 120 percent of expected usage needs deal desk confirmation.
12A discount above the 10 percent a rep can give needs approval, up to the limit for the order size.
13A net order value above USD 1,000,000 needs a sales director review.

  

  

    
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. A usage commit far below expected usage: A USD 60,000 commit against USD 200,000 of expected usage

    
The agent's request. Please check this subscription quote for Northwind Health Partners: Cloud CX 2 for 200 named seats on a one year term, with an annual usage commit of USD 60,000 against USD 200,000 of expected usage, at the net total of USD 319,440. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Commit far below expected usage. A commit of USD 60,000 is below 50 percent of the expected annual usage of USD 200,000.
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  • Estimated price. USD 319440.0 net, of which USD 259440.0 for seats and USD 60000.0 for committed usage. USD 108.1 per seat per month after the 94 percent volume price tier, 0 percent multi-year discount, 0 percent commit discount, discount limit 15 percent, for 200 seats on a 1 year term.
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2. A usage commit far below expected usage: The agent resubmits after fixing the errors

    
The agent's request. I have raised the usage commit to USD 160,000, which is 80 percent of expected usage, and updated the net total to USD 411,440. Please check it again.

    
Verdict: Allowed.

    
    
      
  • Estimated price. USD 411440.0 net, of which USD 259440.0 for seats and USD 152000.0 for committed usage. USD 108.1 per seat per month after the 94 percent volume price tier, 0 percent multi-year discount, 5 percent commit discount, discount limit 15 percent, for 200 seats on a 1 year term.
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3. An add-on below its minimum number of seats: Workforce Engagement for only 20 seats

    
The agent's request. Please check this quote for Alder Creek Insurance: Cloud CX 2 with the Workforce Engagement add-on for 20 named seats on a three year term, at the net total of USD 99,360. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Add-on below its seat minimum. The Workforce Engagement Add-on needs at least 25 seats; 20 were quoted.
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  • Estimated price. USD 99360.0 net, of which USD 99360.0 for seats and USD 0.0 for committed usage. USD 150.0 per seat per month after the 100 percent volume price tier, 8 percent multi-year discount, 0 percent commit discount, discount limit 15 percent, for 20 seats on a 3 year term.
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4. An add-on below its minimum number of seats: The agent resubmits after fixing the errors

    
The agent's request. I have raised the quote to 25 seats, which meets the add-on minimum, at the net total of USD 124,200. Please check it again.

    
Verdict: Allowed.

    
    
      
  • Estimated price. USD 124200.0 net, of which USD 124200.0 for seats and USD 0.0 for committed usage. USD 150.0 per seat per month after the 100 percent volume price tier, 8 percent multi-year discount, 0 percent commit discount, discount limit 15 percent, for 25 seats on a 3 year term.
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5. A stated total that does not match: A net total that is USD 65,000 too low

    
The agent's request. Please check this quote for Harborview Credit Union: Cloud CX 2 with the Digital Messaging add-on for 150 named seats on a three year term, at the net total of USD 588,409.92. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Stated total does not match. The quoted net total of USD 588,409.92 does not match the USD 653,788.80 the validator computed.
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  • Estimated price. USD 653788.8 net, of which USD 653788.8 for seats and USD 0.0 for committed usage. USD 131.6 per seat per month after the 94 percent volume price tier, 8 percent multi-year discount, 0 percent commit discount, discount limit 15 percent, for 150 seats on a 3 year term.
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6. A stated total that does not match: The agent resubmits after fixing the errors

    
The agent's request. I have corrected the net total to the validator figure of USD 653,788.80 and changed nothing else. Please check it again.

    
Verdict: Allowed.

    
    
      
  • Estimated price. USD 653788.8 net, of which USD 653788.8 for seats and USD 0.0 for committed usage. USD 131.6 per seat per month after the 94 percent volume price tier, 8 percent multi-year discount, 0 percent commit discount, discount limit 15 percent, for 150 seats on a 3 year term.
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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 subscription quote for a cloud contact center platform: an edition, an optional add-on, a seat model, and more. Before the quote goes out, the agent sends it to Predictika's validator, which checks all of it together, including the net total the agent states, and reports every problem in one pass.
    2. 
      
  2. I will start with the first request by the agent.
    3. 
      
  3. The agent says. Please check this subscription quote for Northwind Health Partners: Cloud CX 2 for 200 named seats on a one year term. It is ready to send. The rest of the request is on screen.
    4. 
      
  4. Before it goes out, the agent calls the validator.
    5. 
      
  5. Blocked, with one finding, all in one answer. A commit of USD 60,000 is below 50 percent of the expected annual usage of USD 200,000.
    6. 
      
  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. 
      
  7. What this shows: for a committed usage amount judged against expected usage, a rules-based CPQ can do this only with workarounds.
    8. 
      
  8. Now the agent resubmits.
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  9. The corrected request. It changes the annual usage commit to $160,000 and the stated net total to $411,440.
    10. 
      
  10. It calls the validator again.
    11. 
      
  11. This time the validator clears it.
    12. 
      
  12. The earlier finding is cleared.
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  13. One problem caught in one call, fixed in one pass, and a clean $411,440 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.