Strand AI bills predictions in credits. The credits model is intentionally simple so you can predict cost exactly before submitting a job.Documentation Index
Fetch the complete documentation index at: https://docs.strandai.com/llms.txt
Use this file to discover all available pages before exploring further.
How credits work
The platform tiles each slide into fixed 224×224-pixel patches and runs inference per patch, per marker. One credit pays for one (patch × marker) prediction.1 credit = 1 patch × 1 marker. Patch size is fixed at 224 px today;
the credit-to-patch mapping lives in
platform/src/lib/credits/pricing.ts.W × H pixels:
224 × 179 × 5 = 200 480
credits.
Estimating before you submit
The/predict/estimate endpoint (and its SDK wrappers) compute the exact
cost from slide dimensions, with no reservation:
Reservation and refunds
When you callPOST /predict, the platform atomically reserves the
estimated credits against your org balance. The reservation is recorded
on the job (reservedCredits) so:
- In-flight jobs are price-locked. If we change
CREDITS_PER_PATCH_MARKERorPATCH_PXlater, jobs already submitted keep their reserved price. - Failed jobs refund automatically. If a job terminates with status
failed, the reservation is released back to the org balance. - Insufficient balance returns 402. The error body carries the
requiredfield so you know how much to top up.
Buying credits
Credits are sold in prepaid tiers. Today, top-ups are handled by the team. Email support@strandai.com with the volume you need and we’ll provision them.Self-serve top-up via Stripe is in progress and will be surfaced under
Settings → Billing when it ships.
See also
- API reference:
POST /predict/estimate. - API reference:
POST /predict, including 402 / 429 behaviour. - Supported markers: which markers count toward a job’s credit cost.