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Rate limits & credits

How the platform meters usage — credits for actions, quotas for objects.

predictAI doesn't enforce fixed requests-per-second limits. Instead, usage is governed by two mechanisms that map to what actually consumes resources:

Credits meter actions

Compute-heavy actions cost credits, priced per action and charged when the work runs:

  • training runs (per run, scaled by intensity),
  • inference calls,
  • discovery runs and tournaments,
  • large ingestion volumes (streaming events beyond the workspace's included allowance),
  • BYOM uploads and validation.

If your balance can't cover an action you'll get a 402 — the action simply doesn't run. Check your balance and burn rate any time:

curl "$API_BASE/v1/billing/balance" \
  -H "Authorization: Bearer $TOKEN" \
  -H "X-Workspace-Id: $WORKSPACE_ID"

Estimate before you spend with POST /v1/billing/estimate — every chargeable surface can be priced in advance.

Quotas cap objects

Your plan caps how many of each object a workspace can hold: models, pipelines, deployments, goals, and more. Hitting a cap returns a 403 with a message naming the limit. One call shows your live usage counts:

curl "$API_BASE/v1/billing/usage" \
  -H "Authorization: Bearer $TOKEN" \
  -H "X-Workspace-Id: $WORKSPACE_ID"

Being a good citizen

  • Prefer Realtime subscriptions over tight polling loops — training, deployment, and goal events are pushed to you.
  • Batch historical data through Ingestion imports rather than thousands of individual signal/push calls.
  • Cache stable reads (catalogs, plan info); they change rarely.

Full pricing, plans, and quota detail: Billing.

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