Predictika · Warehouse automation system quotes

An AI sales agent's warehouse automation quote, checked before it goes out

An AI sales agent prepares a quote for a Symbotic warehouse automation system: a fleet of SymBot robots, inbound and order preparation cells, and optional BreakPack, FLIB or SymMicro modules. Before it goes out, the agent sends it to Predictika, which checks it against a declarative model of the system and returns a verdict, every reason and the total it computed.

Scope: Symbotic System quotes: SymBot, SymBot XL and SymBot TR robots, inbound cells, order preparation cells, BreakPack, Floor Loaded Inbound Cell and SymMicro. See everything this validator covers

This validator models Symbotic System quotes, not just the scenarios shown below.

  • Robots and items — which robot can carry an item by size and weight (SymBot and SymBot XL for cases, SymBot TR for totes and tri-zone temperature operation).
  • Modules — BreakPack, SymMicro and the Floor Loaded Inbound Cell, and the cells every system needs.
  • Fleet, pallet and price — throughput against fleet size, built pallet height, the discount, and the stated total against the total computed from the modeled prices.

Any Symbotic System quote that touches these rules is in scope — not only the scenarios pictured here. Not covered: software subscriptions, storage structure sizing and services. Symbotic systems are custom-priced: all prices and most rules in this validator are modeled, not published by Symbotic.

The AI sales agentBuilds the warehouse automation system quote 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
Which robot can carry which itemOnly with care
Size and weight limits differ by robot, so each robot needs its own set of size and weight rules, and the list grows with every model.		The robot, the item and its dimensions are in one request and checked together on every call.
Modules that exclude each otherOnly with care
BreakPack, SymMicro and tri-zone operation each depend on the robot chosen, so every module needs a rule that names the robots it can and cannot sit with.		The robot and the modules are fields of the same request and compatibility is checked on every call.
A fleet large enough for the target throughputOnly with workarounds
Throughput depends on the number of robots, so a separate calculation and a rule that compares it with the target are needed.		The target and the fleet are fields of the request and are compared with the computed capacity on every call.
A stated total that must match the computed totalOnly with workarounds
The total is built from many lines, so a separate rule must recompute it and compare it with the stated figure.		The stated total is a field of the request and is compared with the computed total on every call.
Every problem returned in one answerOnly with workarounds
Rules tend to fire as the quote 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 item (90 x 40 x 30 cm) exceeds the payload size this robot can carry.
2The item (50 x 40 x 45 cm) exceeds the payload size this robot can carry.
3An item of 60 lb is close to the 60 lb limit; a person should confirm.
4An item of 65 lb is above the 60 lb payload limit.
5Tri-zone temperature operation needs the SymBot TR; the quoted robot does not support it.
6The SymBot TR retrieves totes; full cases need a SymBot or SymBot XL.
7BreakPack is added to a case-picking storage system; it cannot be quoted with the SymBot TR.
8A SymMicro system is quoted with the SymBot TR.
9The system needs at least 1 inbound cell; the quote has 0.
1012,000 cases per hour needs more robots; 100 robots give 10,000 cases per hour.
11A built pallet of 250 cm needs stability and trailer fit confirmed by a person.
12A built pallet height of 270 cm is above the 260 cm maximum.
13A fleet of 160 robots needs the commissioning schedule confirmed by a person.
14The quote states USD 10,000,000 in total; the computed total is USD 10,400,000.
15A discount of 8 percent is above 5 percent and needs sales management approval.
16A discount of 15 percent is above the 12 percent maximum.

  

  

    
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. Long items, throughput and price: A case-picking system for a grocery distribution center with long cases, a tall pallet and a deep discount

    
The agent's request. Please quote a Symbotic System with 100 SymBot robots, no inbound cells and 3 order preparation cells, for a target of 12,000 cases per hour, handling cases of 90 x 60 x 30 cm and 40 lb, with a built pallet height of 270 cm, a 15 percent discount, for a total of USD 7,310,000. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Item too large for the robot. The item (90 x 60 x 30 cm) exceeds the payload size this robot can carry.
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  • Pallet too tall. A built pallet height of 270 cm is above the 260 cm maximum.
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  • No inbound cell. The system needs at least 1 inbound cell; the quote has 0.
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  • Fleet too small for the target. 12,000 cases per hour needs more robots; 100 robots give 10,000 cases per hour.
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  • Discount over the maximum. A discount of 15 percent is above the 12 percent maximum.
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2. Long items, throughput and price: The agent resubmits after fixing the errors

    
The agent's request. Please quote a Symbotic System with 120 SymBot XL robots, 2 inbound cells and 3 order preparation cells, for a target of 12,000 cases per hour, handling cases of 90 x 60 x 30 cm and 40 lb, with a built pallet height of 240 cm, a 5 percent discount, for a total of USD 11,875,000. It is ready to send.

    
Verdict: Allowed.

    
    
      
  • System summary. 120 robots giving 12,000 cases per hour, total USD 11,875,000 after 5 percent discount.
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3. Cold-chain tote system: A cold-chain tote system for a grocery distribution center with BreakPack

    
The agent's request. Please quote a SymMicro system with 40 SymBot robots, 2 inbound cells and 2 order preparation cells, for a target of 3,500 cases per hour, handling totes of 50 x 40 x 30 cm and 30 lb, with a built pallet height of 200 cm, tri-zone temperature operation and BreakPack, for a total of USD 7,200,000. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Multi-temperature needs SymBot TR. Tri-zone temperature operation needs the SymBot TR; the quoted robot does not support it.
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  • SymMicro needs SymBot TR. A SymMicro system is quoted with the SymBot TR.
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4. Cold-chain tote system: The agent resubmits after fixing the errors

    
The agent's request. Please quote a SymMicro system with 40 SymBot TR robots, 2 inbound cells and 2 order preparation cells, for a target of 3,500 cases per hour, handling totes of 50 x 40 x 30 cm and 30 lb, with a built pallet height of 200 cm, tri-zone temperature operation and BreakPack, for a total of USD 7,000,000. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • BreakPack needs a case-picking system. BreakPack is added to a case-picking storage system; it cannot be quoted with the SymBot TR.
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5. Cold-chain tote system: The agent resubmits after fixing the errors

    
The agent's request. Please quote a SymMicro system with 40 SymBot TR robots, 2 inbound cells and 2 order preparation cells, for a target of 3,500 cases per hour, handling totes of 50 x 40 x 30 cm and 30 lb, with a built pallet height of 200 cm, tri-zone temperature operation, for a total of USD 6,400,000. It is ready to send.

    
Verdict: Allowed.

    
    
      
  • System summary. 40 robots giving 4,000 cases per hour, total USD 6,400,000 after 0 percent discount.
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6. Heavy item and stated total: A system for heavy cases with a stated total

    
The agent's request. Please quote a Symbotic System with 100 SymBot robots, 2 inbound cells and 3 order preparation cells, for a target of 9,000 cases per hour, handling cases of 50 x 40 x 30 cm and 65 lb, with a built pallet height of 200 cm, for a total of USD 9,800,000. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Item over the payload weight. An item of 65 lb is above the 60 lb payload limit.
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  • Stated total does not match. The quote states USD 9,800,000 in total; the computed total is USD 10,400,000.
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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 quote for a Symbotic warehouse automation system: a fleet of SymBot robots, inbound and order preparation cells, optional BreakPack, and more. Before it goes out, the agent sends it to Predictika, which checks it against a declarative model of the system and returns a verdict, every reason and the total it computed.
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  2. I will start with the first request by the agent.
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  3. The agent says. Please quote a Symbotic System with 100 SymBot robots, no inbound cells and 3 order preparation cells, for a target of 12,000 cases per hour. It is ready to send. 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 five findings, all in one answer. The item (90 x 60 x 30 cm) exceeds the payload size this robot can carry. A built pallet height of 270 cm is above the 260 cm maximum. The system needs at least 1 inbound cell; the quote has 0. The other two are on screen.
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  6. The validator returned five 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 a fleet large enough for the target throughput, 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 robot to SymBot XL, the robots to 120, the inbound cells to 2, the built pallet height to 240 cm, the discount to 5 percent and the total stated on the quote to $11,875,000.
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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 five earlier findings are cleared.
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  13. Five problems caught in one call, fixed in one pass, and a clean $11,875,000 quote. That is the value of Predictika's validator: catching mistakes before they reach the customer. Now you can try the other scenarios yourself.
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