Predictika · Analytics software tier and capacity configuration

An AI sales agent's analytics subscription order, checked before it goes out

An AI sales agent prepares an order for a Qlik Cloud Analytics subscription with a tier, users, data capacity packs, the customer's largest app and the features the customer needs. Before it goes out, the agent sends it to Predictika, which checks it against a declarative model of the public pricing page and returns a verdict, every reason and the figures it computed.

Scope: Qlik Cloud Analytics orders on the Starter, Standard, Premium and Enterprise tiers: users, data capacity and packs, maximum app size, and tier-only features. See everything this validator covers

This validator models Qlik Cloud Analytics tier orders, not just the scenarios shown below.

  • Users and data capacity — Starter includes 10 users with more available as individual purchases and a fixed 10 GB with no additional capacity; Standard starts at 25 GB with 25 GB increments; Premium starts at 50 GB with 25 GB or 250 GB packs; Enterprise starts at 250 GB. The capacity the customer needs and the capacity stated on the quote are compared with what the tier and packs give.
  • App size — the 5 GB maximum app size on Starter and the 10 GB maximum on Premium; Enterprise lists 15 GB apps as standard, and larger apps need a person to confirm.
  • Tier features — managed and shared spaces and unstructured data with GenAI from Standard; predictive analytics, anonymous access, SAP data extraction and data lineage connectors from Premium; multi-region tenants on Enterprise only.

Any Qlik Cloud Analytics order that touches these rules is in scope — not only the scenarios pictured here. Not covered: prices (the public page gives only starting monthly prices, so no price build-up or line-item quote is produced), Standard app size, other Qlik products, and any tier detail not listed above.

The AI sales agentBuilds the subscription order 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
Capacity that grows in fixed packs and starts at a different size per tierOnly with care
The starting capacity and the allowed pack sizes differ by tier, so each tier needs its own calculation and a rule against packs it does not sell.		The tier, packs and capacity needed are in one request and the capacity is computed and compared on every call.
A stated capacity that disagrees with the tier and packsOnly with workarounds
The capacity is derived from the tier and packs; checking a figure stated on the quote against it takes extra formulas that interact with the pack rules.		The stated figure is one more field in the request and is compared with the computed capacity on every call.
Features that appear only from a certain tierEasy
A compatibility rule per feature and tier; routine in a product-rules CPQ.		The same rules, checked together with all the others on every call.
Limits that differ by tier (users, app size)Only with care
Each limit applies to one tier only, so the rule has to be scoped to the tier and kept in step as tiers change.		The tier, users and app size are compared 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.

    
1Starter includes 10 users and the order has 0 additional individual users purchased; the customer needs 12 users.
2No additional data capacity is available for purchase on Starter; the order has capacity packs.
3The customer needs 15 GB of data for analysis; the quoted tier and packs give 10 GB.
4The customer needs 80 GB of data for analysis; the quoted tier and packs give 75 GB.
5Standard adds data capacity in 25 GB increments; the 250 GB packs are listed for Premium, and the order has 1 of them on Standard.
6The customer needs 70 GB of data for analysis; the quoted tier and packs give 50 GB.
7The quote states 100 GB of data for analysis; the quoted tier and packs give 75 GB.
8Managed and shared spaces are listed from the Standard tier; the order is on Starter.
9Leveraging unstructured data and GenAI is listed from the Standard tier; the order is on Starter.
10Predictive analytics powered by automated machine learning is listed from the Premium tier.
11Anonymous (public) access is listed from the Premium tier.
12Data extraction from SAP systems into Qlik Cloud is listed from the Premium tier.
13Data lineage connectors are listed from the Premium tier.
14Multi-region tenants are listed only on the Enterprise tier.
15The customer needs 400 GB; Enterprise starts at 250 GB and its pricing is by quote, so a person should confirm the capacity and price.
16The customer has an app of 20 GB; Enterprise lists 15 GB apps as standard and larger apps as a larger-apps option, so a person should confirm it.
17The customer has an app of 8 GB; Starter allows a maximum app size of 5 GB.
18The customer has an app of 12 GB; Premium allows a maximum app size of 10 GB.
19The quote states 10 GB of data for analysis; the quoted tier and packs give 35 GB.
20Starter includes 10 users and the order has 0 additional individual users purchased; the customer needs 15 users.
21The customer has an app of 7 GB; Starter allows a maximum app size of 5 GB.

  

  

    
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. Starter team: A Starter order for 18 users with a capacity pack, an 8 GB app and managed spaces

    
The agent's request. Please prepare a Qlik Cloud Analytics order on the Starter tier for 18 users and a customer who needs 15 GB of data for analysis, with one 25 GB capacity pack, the customer's largest app being 8 GB, and needing managed and shared spaces. The order states 35 GB of data for analysis. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Starter cannot add data capacity. No additional data capacity is available for purchase on Starter; the order has capacity packs.
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  • Starter users above those included and purchased. Starter includes 10 users and the order has 0 additional individual users purchased; the customer needs 18 users.
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  • App size above the Starter limit. The customer has an app of 8 GB; Starter allows a maximum app size of 5 GB.
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  • Managed spaces need Standard or above. Managed and shared spaces are listed from the Standard tier; the order is on Starter.
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2. Starter team: The agent resubmits after fixing the errors

    
The agent's request. Please prepare a Qlik Cloud Analytics order on the Standard tier for 18 users and a customer who needs 40 GB of data for analysis, with one 25 GB capacity pack, the customer's largest app being 8 GB, and needing managed and shared spaces. The order states 50 GB of data for analysis. It is ready to send.

    
Verdict: Allowed.

    
    
      
  • Order summary. Order with 50 GB of data for analysis (25 GB included at the start of the tier).
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3. Premium features on Standard: A Standard order with a 250 GB pack, predictive analytics, anonymous access and SAP extraction

    
The agent's request. Please prepare a Qlik Cloud Analytics order on the Standard tier for 120 users and a customer who needs 300 GB of data for analysis, with two 25 GB capacity packs and one 250 GB capacity pack, the customer's largest app being 6 GB, and needing managed and shared spaces, predictive analytics, anonymous access and SAP data extraction. The order states 325 GB of data for analysis. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Standard adds capacity in 25 GB increments. Standard adds data capacity in 25 GB increments; the 250 GB packs are listed for Premium, and the order has 1 of them on Standard.
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  • Predictive analytics needs Premium or above. Predictive analytics powered by automated machine learning is listed from the Premium tier.
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  • Anonymous access needs Premium or above. Anonymous (public) access is listed from the Premium tier.
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  • SAP data extraction needs Premium or above. Data extraction from SAP systems into Qlik Cloud is listed from the Premium tier.
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4. Premium features on Standard: The agent resubmits after fixing the errors

    
The agent's request. Please prepare a Qlik Cloud Analytics order on the Premium tier for 120 users and a customer who needs 300 GB of data for analysis, with one 250 GB capacity pack, the customer's largest app being 6 GB, and needing managed and shared spaces, predictive analytics, anonymous access and SAP data extraction. The order states 300 GB of data for analysis. It is ready to send.

    
Verdict: Allowed.

    
    
      
  • Order summary. Order with 300 GB of data for analysis (50 GB included at the start of the tier).
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5. Large deployment: A Premium order for 400 GB with a 12 GB app and multi-region tenants

    
The agent's request. Please prepare a Qlik Cloud Analytics order on the Premium tier for 400 users and a customer who needs 400 GB of data for analysis, with one 250 GB capacity pack, the customer's largest app being 12 GB, and needing data lineage connectors and multi-region tenants. The order states 300 GB of data for analysis. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Data capacity below the need. The customer needs 400 GB of data for analysis; the quoted tier and packs give 300 GB.
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  • App size above the Premium limit. The customer has an app of 12 GB; Premium allows a maximum app size of 10 GB.
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  • Multi-region tenants need Enterprise. Multi-region tenants are listed only on the Enterprise tier.
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6. Large deployment: The agent resubmits after fixing the errors

    
The agent's request. Please prepare a Qlik Cloud Analytics order on the Enterprise tier for 400 users and a customer who needs 200 GB of data for analysis, the customer's largest app being 12 GB, and needing data lineage connectors and multi-region tenants. The order states 250 GB of data for analysis. It is ready to send.

    
Verdict: Allowed.

    
    
      
  • Order summary. Order with 250 GB of data for analysis (250 GB included at the start of the tier).
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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 an order for a Qlik Cloud Analytics subscription with a tier, users, data capacity packs, the customer's largest app and the features the customer needs. Before it goes out, the agent sends it to Predictika, which checks it against a declarative model of the public pricing page 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 prepare a Qlik Cloud Analytics order on the Standard tier for 120 users and a customer who needs 300 GB of data for analysis. The order states 325 GB of data for analysis. 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 four findings, all in one answer. Standard adds data capacity in 25 GB increments; the 250 GB packs are listed for Premium, and the order has 1 of them on Standard. Predictive analytics powered by automated machine learning is listed from the Premium tier. Anonymous (public) access is listed from the Premium tier. The other one is on screen.
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  6. The validator returned four 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 capacity that grows in fixed packs and starts at a different size per tier, 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 tier to premium, the 25 GB capacity packs to 0 and the data for analysis as stated on the quote to 300 GB.
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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. All four earlier findings are cleared.
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  13. Four 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.