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Hollerith meters input and output rows for successful jobs. Input rows are rows a job processes; output rows are prediction rows returned. Free applies separate input and output allowances. Paid plans combine both as billable rows.

Pay for what you use

Example

A context-backed predict counts only the rows to score as input because the fitted context is already stored. Input and output row counts are therefore equal. On 200 000 training rows and 50 000 rows to score:
The fit is paid once. Each predict against that context pays twice its own batch. Free shows separate input and output meters. Paid plans show their combined billable rows.

Plans

Allowances are organization-wide: every key, member and job kind draws on the same counters. Free applies its input and output allowances independently. Paid plans pool both counters. Plans are not self-serve. A Hollerith administrator provisions changes (see Request higher limits). An owner of a Free organization can add a payment method, enable paid overage and set a monthly dollar ceiling.

Overage and credits

Spend order is fixed: included allowance first, then organization-level dollar credits, then paid overage. Overage is off by default. With overage off, jobs stop as soon as the plan’s input or output cap or the daily quota is exhausted, whichever comes first, not when the billed pooled total in the table above is crossed. Enabling overage and setting a monthly dollar ceiling lets jobs continue past the included allowance, drawing on credits first and then paid overage up to that ceiling.

Daily quota

The daily quota counts input rows only. Output rows bill but do not draw on it. A context-backed predict of 50 000 rows spends 50 000 of quota and bills 100 000. Quota is reserved when a job is submitted and released when it completes, so a burst of submits can hit quota_exceeded before any of them runs.

Request higher limits

If you need higher usage than your plan includes, email founders@monarcha.ai with the volumes you have in mind.

Next steps

Limits

Learn about the constraints Hollerith is optimized for

Data handling and retention

What we keep, and for how long