Pricing

A price that fits how you actually use it.

ML.ai Inference is scoped to your traffic and your savings target, not a plan picked off a page. Book a call and we’ll size it together: what it costs, what it saves, and where the number lands for your workload.

ML.ai is a product of Pixis.ai, backed by SoftBank Vision Fund and General Atlantic.

Monthly model spend

$50,000

$5k$250k

You save (3045%)

$15,000$22,500

per month, same eval bar

ML.ai Code plans

A flat monthly price, plus usage only
past what’s included.

No per-seat licenses, no charge for reviewers or admins who never touch a model. Each plan includes a fixed amount of execution usage at $0 fee, with a completion fee only on what runs past it.

Verify

For a workload proving itself before anything is billed.

$0for 30 days

Signal plus first task free, up to $5

  • 1 trigger user
  • Public Signal
  • 100 private Signals
  • 5 deep reviews
  • First $5 task once
Install

Builder

For an individual doing deep verification and repair PRs.

$20/mo

$15 execution included

  • 1 builder
  • $15 included usage
  • Full GitHub automation
  • CLI/IDE
  • 3 concurrent agents
Install
Best launch plan

Team

For up to 50 builders running verified execution on a shared budget.

$99/workspace/mo

$75 pooled execution

  • Up to 50 trigger users
  • $75 pooled usage
  • 10 concurrent agents
  • Team rules and budgets
  • CI Rescue and issue-to-PR
Install

Scale

For higher concurrency with SSO/SCIM and cost centers.

$499/workspace/mo

$350 pooled execution

  • Up to 250 trigger users
  • $350 usage
  • SSO/SCIM
  • Cost centers
  • 50 concurrent agents
Install

Enterprise

For VPC, on-prem, or BYOK deployments with SLA and procurement controls.

Customnegotiated rate

Committed usage

  • Committed usage
  • Custom policy
  • BYOK, VPC/on-prem
  • Data residency
  • Negotiated fee
Talk to sales

Pricing questions.

For anything else, the pilot call is 30 minutes and free.

Stop picking a model, and start running a harness that keeps lowering your bill.

Bring one workload. We’ll run it through the shadow phase, side by side with what you have today.