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Every successful generation consumes credits from your organization’s balance. This page documents the exact behavior that ships today — pricing specifics are set per-tier and per-deal; contact sales for a rate card.

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What costs credits

Today, only successful generation runs cost credits:
  • POST /excel/generate, /word/generate, /slides/generate
  • POST /excel/analyze
  • POST /text/humanize, /text/rewrite, /text/new-content
Everything else — GET /runs, /tasks, /verify, /webhooks, POST /files (upload), DELETE /images/{id}, edit-URL rendering, preflight — is free. File storage and bandwidth are not billed separately in v1.

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How a run is priced

The credits_used returned on every completed response is the authoritative charge for that run. It’s derived from the real model-token usage for all LLM turns inside the run plus the agent’s tool activity. We don’t publish a static per-format rate card in v1. Prices depend on:
  • The models used during the run (varies by request shape and tier).
  • How much the agent had to iterate — a short prompt on a small sheet costs a fraction of a multi-sheet model that took 20 agent turns.
  • Whether preflight rejected the call (rejection is free; see Preflight).
If you need budgeting numbers for procurement or capacity planning, reach out — we’ll share the pricing worksheet for your tier.

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Balance check before a run

Before a generation request is accepted, we verify your balance is above a small safety floor. If it isn’t, the API returns: 
402 Insufficient credits
{
  "success": false,
  "error": "insufficient_credits",
  "message": "Insufficient credits. Required: N, balance: M."
}
The Required value is the minimum we need on file before starting. It’s deliberately conservative so we never start work you can’t afford to complete. The actual deduction after success is usually smaller or similar — it’s the real usage, not the pre-flight estimate. This check runs before the preflight LLM and the document pipeline, so you never pay for a run that was rejected for insufficient balance.

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When you’re charged

EventCredits charged?
Request rejected by balance check (402)No
Request rejected by preflight (preflight_failed)No
Request rejected by permissions / authNo
Agent runs, succeedsYes — credits_used on response
Agent runs, fails mid-executionNo (v1 behavior)
Sync auto-promoted to async then succeeds on the workerYes
Async worker job failsNo
v1 behavior for failures: if a run crashes after starting, we don’t charge. This is deliberately customer-friendly; if it ever changes we’ll update this page and the changelog before enforcing.

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Top-ups and balance visibility

Top-ups are applied immediately — the next request sees the new balance. Your balance is visible at app.overten.ai → Settings → Billing, or by contacting support with your org_id. Individual run costs are returned on the credits_used field of every completed response, so you can reconcile spend from your own logs.

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Refunds

If a completed run produced something unusable — wrong format, corrupted output, an edge case that slipped through preflight — open a support ticket with the run_id. We’ll pull the internal ledger row, verify what happened, and issue a credit on a case-by-case basis. We don’t refund “I didn’t like the result” — the agent produced the artifact you asked for, even if the prompt was underspecified. Better prompting, not post-hoc refunds, is the fix there. Work with support on patterns that misbehave and we’ll tune the agents.

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Audit trail

Every credit movement — deduction, top-up, refund — is written to an internal ledger keyed by (org_id, run_id, timestamp, delta). For billing disputes, reference the run_id from your response payload and support can pull the matching row. Individual run responses and GET /runs/{run_id} both expose credits_used, so you can reconcile your local records without needing dashboard access.

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Observability

Per-run cost attribution — which turn, which tool, which model — is visible to our team via our observability backend. If you’re debugging why a specific run cost what it did, file a support ticket with the run_id and we can walk you through the breakdown. Customer-side observability export (your own Langfuse / Datadog destination) is available on enterprise tier. Contact sales for setup.