Lightly · FinOps Profile

Lightly Ai Finops

FinOps view of LightlyOne platform spend. Lightly bills via plan subscription (free Community, paid Team, custom Enterprise) rather than a granular per-call meter, so cost is driven by the chosen tier and the dataset-size / media / collaboration entitlements it unlocks. The main cost levers are input dataset volume, LightlyOne Worker compute-run frequency, and cloud-storage egress on the customer's own S3 / GCS / Azure datasource (paid to the cloud provider, not Lightly). The open-source `lightly` SDK is free. Figures are not reconciled against a current rate card.

Lightly Ai Finops is the FinOps profile for Lightly on the APIs.io network, aligned with the FinOps Foundation Framework.

It defines 5 billable meters, billed in USD, on a monthly cycle, and pricing category subscription-based.

The profile maps 8 FOCUS columns for cost-allocation reporting.

Tagged areas include AI, Computer Vision, Data Curation, Active Learning, and Embeddings.

Category: AI and Machine Learning Pricing: Subscription-Based Billing: Monthly FOCUS v1.3
AIComputer VisionData CurationActive LearningEmbeddingsFinOpsCost ManagementFOCUS

Framework Alignment

Framework
FinOps Foundation Framework
Data Spec
FOCUS v1.3

Charge Categories

UsagePurchase

FOCUS Columns

BillingCurrency
USD
ChargeCategory
Usage
InvoiceIssuerName
Lightly
PricingCategory
Subscription-Based
ProviderName
Lightly
PublisherName
Lightly
ServiceCategory
AI and Machine Learning
ServiceName
LightlyOne

Meters

plan_subscription
Unit: subscription
Monthly platform subscription for the selected tier (Team / Enterprise).
input_dataset_samples
Unit: samples
Number of input samples curated, bounded by the plan dataset-size quota.
worker_runs
Unit: runs
LightlyOne Worker selection / active-learning compute runs executed.
stored_data_bytes
Unit: bytes
Data and embeddings stored against the platform / datasource.
datasource_egress_bytes
Unit: bytes
Cloud-storage egress on the customer datasource (billed by the cloud provider, not Lightly).

Sources