Predictika · GPU cluster reservations

An AI sales agent's GPU cluster reservation, checked before it goes out

An AI sales agent prepares a reservation request for a Lambda 1-Click Cluster: GPU type and region, number of GPUs, term in weeks, filesystem and S3 adapter, any special price, and the rate, total and free capacity it will state to the customer. Before it goes out, the agent sends it to Predictika, which checks it against a declarative model of Lambda's published cluster rules and a capacity ledger and returns a verdict, every reason and the computed price.

Scope: Lambda 1-Click Cluster reservations on HGX B200 and H100: cluster size and node multiple, term, published volume price tiers, free capacity, filesystem region and S3 adapter, special pricing, orchestration and stated figures. See everything this validator covers

This validator models Lambda 1-Click Cluster reservation requests, not just the scenarios shown below.

  • Cluster and term — a minimum of 16 GPUs built from 8-GPU nodes, whole-week terms of at least 2 weeks, published prices up to 1 year, and the 512 GPU self-serve size above which sales takes over.
  • Price and capacity — the published per-GPU-hour price tier for the cluster size, the computed list price, discount and net, and the GPUs free in the region and quarter against a capacity ledger, with a thin margin sent for approval.
  • Region, storage and services — filesystems in the same region as the cluster, the S3 adapter available only in three regions, no data transfer charges, no extension of an existing reservation, and managed Kubernetes or Slurm priced by sales.
  • Special price, payment and stated figures — a special price needing the deal desk or refused above 15 percent, payment terms beyond 10 days, and the rate, total and free capacity the agent states against the computed ones.

Any reservation that touches these rules is in scope, not only the scenarios pictured here. Prices, tiers, minimums and region rules follow Lambda public pages; the capacity ledger, the 15 percent deal desk limit, the 512 GPU ceiling and the 8-GPU node multiple are Predictika assumptions, not Lambda facts. Not covered: Private Cloud, Hyperscale, on-demand instances, sales tax and contract terms.

The AI sales agentBuilds the reservation request 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
A reservation where fixing one field breaks anotherOnly with workarounds
Moving a cluster to a region that offers the S3 adapter changes the free capacity, the filesystem match and, when the size shrinks to fit, the price tier. Rules fire one at a time, so the rep fixes one error and meets the next.		Every rule is checked on every call, in whatever order the choices arrive, so all ten holds come back at once and the resubmission is checked as a whole.
A price tier that depends on the cluster sizeOnly with care
Each tier needs its own price rule, and the stated rate has to be compared by hand after every resize. Cutting a cluster below a boundary silently changes the rate.		The tier is data in the request; the rate and total are computed on every call and compared with what the agent states.
Free capacity by region and quarterOnly with workarounds
A capacity ledger by region and quarter is a table outside the rules; each combination needs a lookup and a margin check that someone must keep in step.		The ledger is part of the model; free GPUs and the margin left are computed for the chosen region and quarter.
Approvals beside outright holdsOnly with care
A special price, a term over a year, a size above self-serve, sales-priced orchestration and slow payment each route to a different approver and must not be mistaken for blocks.		Approvals and blocks are different findings in one answer: block if any hold exists, otherwise needs approval.
Figures the agent states itselfOnly with workarounds
The stated rate, total and free capacity are free text or fields outside the rules, so a separate comparison is needed for each.		The stated figures are fields of the request and are compared with the computed ones on every call.

  

  

    
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 request; approval findings need a person to sign off; everything else is computed.

    
1400 GPUs is more than the 384 GPUs free in us-midwest-1 B200 for Q4 2026.
2The request states 450 GPUs free in us-midwest-1 B200 for Q4 2026, but the capacity ledger shows 384.
3The filesystem is in us-east-2 but the cluster is in us-midwest-1; a filesystem must be in the same region as the cluster.
4The request states $8.87 per GPU hour, but the published price for 64 GPUs is $9.36.
512 GPUs is not a multiple of 8; a cluster is built from 8-GPU HGX nodes.
612 GPUs is below the 16 GPU minimum for a 1-Click Cluster.
7A reservation of 1 week(s) is below the 2 week minimum.
8The quote includes a data transfer charge; Lambda has no ingress or egress fees.
9A cluster reservation cannot be extended or renewed; a new reservation request is required.
10A special price of 20 percent below list is above the 15 percent the deal desk can approve.
11This reservation leaves only 32 GPUs free in us-midwest-1 B200 for Q4 2026; confirm with capacity planning.
1260 weeks is beyond the 1 year Lambda publishes prices for; a longer term is priced by sales.
13A special price of 10 percent below list needs deal desk approval; the published tiers are list prices.
14Managed Slurm has no published price; sales prices it as an add-on.
15Payment terms of 30 days; the standard is to pay the invoice within 10 days of approval.
16The S3 adapter is offered only in us-east-2, us-east-3 and us-midwest-2, not in us-west-3.
17The request states a total of $10.00, but the validator computes $805,109.76.
18576 GPUs is above the 512 GPU self-serve reservation size; larger clusters are arranged with sales.

  

  

    
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. Region, storage, capacity and price: A 420-GPU B200 cluster in us-midwest-1 for one week, with a filesystem in us-west-3, the S3 adapter, a data transfer charge, a 20 percent special price and three figures of its own

    
The agent's request. Please reserve a cluster of 420 GPUs (B200 in us-midwest-1 starting Q4 2026) for 1 week(s), with a filesystem in us-west-3, the S3 adapter, a special price of 20 percent below list and a data transfer charge. I will tell the customer a rate of $9.86 per GPU hour, a total of $1,000,000.00, and 450 GPUs free. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Not a whole number of nodes. 420 GPUs is not a multiple of 8; a cluster is built from 8-GPU HGX nodes.
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  • Term below two weeks. A reservation of 1 week(s) is below the 2 week minimum.
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  • More GPUs than are free. 420 GPUs is more than the 384 GPUs free in us-midwest-1 B200 for Q4 2026.
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  • Filesystem in another region. The filesystem is in us-west-3 but the cluster is in us-midwest-1; a filesystem must be in the same region as the cluster.
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  • S3 adapter not offered in the region. The S3 adapter is offered only in us-east-2, us-east-3 and us-midwest-2, not in us-west-3.
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  • Data transfer charge quoted. The quote includes a data transfer charge; Lambda has no ingress or egress fees.
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  • Special price above the deal desk limit. A special price of 20 percent below list is above the 15 percent the deal desk can approve.
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  • Stated rate does not match. The request states $9.86 per GPU hour, but the published price for 420 GPUs is $8.87.
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  • Stated total does not match. The request states a total of $1,000,000.00, but the validator computes $500,693.76.
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  • Stated free capacity does not match. The request states 450 GPUs free in us-midwest-1 B200 for Q4 2026, but the capacity ledger shows 384.
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2. Region, storage, capacity and price: The agent resubmits after fixing the errors

    
The agent's request. Please reserve a cluster of 192 GPUs (B200 in us-east-2 starting Q4 2026) for 4 week(s), with a filesystem in us-east-2 and the S3 adapter. I will tell the customer a rate of $9.36 per GPU hour, a total of $1,207,664.64, and 256 GPUs free. It is ready to send.

    
Verdict: Allowed.

    
    
      
  • Capacity and price tier. B200 us-east-2 Q4 2026 has 256 GPUs free of 768; the published price at 192 GPUs is $9.36 per GPU hour.
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3. Approvals: A 576-GPU B200 cluster for 60 weeks with managed Slurm, a 10 percent special price and 30 day payment terms

    
The agent's request. Please reserve a cluster of 576 GPUs (B200 in us-midwest-1 starting Q1 2027) for 60 week(s), with a special price of 10 percent below list, managed Slurm and 30 day payment terms. I will tell the customer a rate of $8.87 per GPU hour, a total of $46,349,936.64, and 640 GPUs free. It is ready to send.

    
Verdict: Needs approval.

    
    
      
  • Term beyond one year. 60 weeks is beyond the 1 year Lambda publishes prices for; a longer term is priced by sales.
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  • Above the self-serve size. 576 GPUs is above the 512 GPU self-serve reservation size; larger clusters are arranged with sales.
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  • Special price needs the deal desk. A special price of 10 percent below list needs deal desk approval; the published tiers are list prices.
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  • Managed orchestration is sales-priced. Managed Slurm has no published price; sales prices it as an add-on.
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  • Payment terms beyond 10 days. Payment terms of 30 days; the standard is to pay the invoice within 10 days of approval.
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  • Capacity and price tier. B200 us-midwest-1 Q1 2027 has 640 GPUs free of 1,280; the published price at 576 GPUs is $8.87 per GPU hour.
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4. Approvals: The agent resubmits after the approvals are addressed

    
The agent's request. Please reserve a cluster of 512 GPUs (B200 in us-midwest-1 starting Q1 2027) for 52 week(s). I will tell the customer a rate of $8.87 per GPU hour, a total of $39,674,019.84, and 640 GPUs free. It is ready to send.

    
Verdict: Allowed.

    
    
      
  • Capacity and price tier. B200 us-midwest-1 Q1 2027 has 640 GPUs free of 1,280; the published price at 512 GPUs is $8.87 per GPU hour.
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5. Capacity margin and price tier: A 120-GPU cluster in us-west-3 where 128 are free, stating the 256-GPU rate

    
The agent's request. Please reserve a cluster of 120 GPUs (B200 in us-west-3 starting Q4 2026) for 8 week(s). I will tell the customer a rate of $8.87 per GPU hour, a total of $1,509,580.80, and 128 GPUs free. It is ready to send.

    
Verdict: Blocked.

    
    
      
  • Stated rate does not match. The request states $8.87 per GPU hour, but the published price for 120 GPUs is $9.36.
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  • Thin capacity margin. This reservation leaves only 8 GPUs free in us-west-3 B200 for Q4 2026; confirm with capacity planning.
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6. Capacity margin and price tier: The agent resubmits after fixing the errors

    
The agent's request. Please reserve a cluster of 56 GPUs (B200 in us-west-3 starting Q4 2026) for 8 week(s). I will tell the customer a rate of $9.86 per GPU hour, a total of $742,103.04, and 128 GPUs free. It is ready to send.

    
Verdict: Allowed.

    
    
      
  • Capacity and price tier. B200 us-west-3 Q4 2026 has 128 GPUs free of 512; the published price at 56 GPUs is $9.86 per GPU hour.
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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 reservation request for a Lambda 1-Click Cluster: GPU type and region, number of GPUs, term in weeks, and more. Before it goes out, the agent sends it to Predictika, which checks it against a declarative model of Lambda's published cluster rules and a capacity ledger and returns a verdict, every reason and the computed price.
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  2. I will start with the first request by the agent.
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  3. The agent says. Please reserve a cluster of 420 GPUs (B200 in us-midwest-1 starting Q4 2026) for 1 week(s), with a filesystem in us-west-3. I will tell the customer a rate of $9.86 per GPU hour, a total of $1,000,000.00, and 450 GPUs free. 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 ten findings, all in one answer. 420 GPUs is not a multiple of 8; a cluster is built from 8-GPU HGX nodes. A reservation of 1 week(s) is below the 2 week minimum. 420 GPUs is more than the 384 GPUs free in us-midwest-1 B200 for Q4 2026. The other seven are on screen.
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  6. The validator returned ten 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 reservation are checked against each other and against the stated total.
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  7. What this shows: for free capacity by region and quarter, 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 cluster to B200 in us-east-2 starting Q4 2026, the GPUs to 192, the term to 4 weeks, the filesystem region to us-east-2, the stated rate to 9.36, the stated total to $1,207,664.64 and the stated Free GPUs to 256. It removes the special price and data transfer charge.
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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. All ten earlier findings are cleared.
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  14. Ten problems caught in one call, fixed in one pass, and a clean $1,207,664.64 reservation. That is the value of Predictika's validator: catching mistakes before it is confirmed.
    15.