specification: FinOps Framework
specificationVersion: '1.0'
schema: https://www.finops.org/framework/
provider: Segments.ai
providerId: segments-ai
created: '2026-06-21'
modified: '2026-06-21'
reconciled: false
tags:
- Data Labeling
- Computer Vision
- Point Cloud
- Annotation
- Machine Learning
- FinOps
- Cost Management
- FOCUS
description: >-
  FinOps view of Segments.ai spend. Segments.ai bills as an annual platform
  subscription whose primary cost driver is labeling-hours consumed per year
  (Core, Fusion, Enterprise tiers), with unlimited seats and projects. The REST
  API and Python SDK are not separately metered, so API-side cost optimization
  focuses on controlling how much paid labeling work is generated - dataset
  scope, sample volume, prelabeling/active learning to reduce manual hours, and
  reuse of releases - rather than on per-call charges.
notes: >-
  Per-hour and included-hours figures reflect the public pricing page at
  capture time and are subject to negotiation for Fusion/Enterprise; verify
  committed hours and overage terms with Segments.ai during reconciliation.
sources:
- https://segments.ai/pricing
- https://docs.segments.ai
- https://focus.finops.org/focus-specification/v1-3/
alignedWith:
  framework: FinOps Foundation Framework
  frameworkUrl: https://www.finops.org/framework/
  dataSpec: FOCUS
  dataSpecVersion: '1.3'
  dataSpecUrl: https://focus.finops.org/focus-specification/v1-3/
publisherName: Segments.ai
serviceCategory: AI and Machine Learning
billingModel:
  pricingCategory: Subscription-Based
  billingFrequency: Annual
  billingCurrency: USD
  chargeCategories:
  - Usage
  - Purchase
  - Adjustment
focusColumns:
  ServiceName: Segments.ai
  ServiceCategory: AI and Machine Learning
  ProviderName: Segments.ai
  PublisherName: Segments.ai
  InvoiceIssuerName: Segments.ai
  BillingCurrency: USD
  ChargeCategory: Usage
  PricingCategory: Subscription-Based
meters:
- name: annual_subscription
  description: Annual platform subscription fee for the selected plan tier (Core, Fusion, Enterprise).
  unit: subscription
  aggregation: sum
  dimensions:
  - account
  - plan
- name: labeling_hours
  description: Labeling-hours consumed against the annual usage allotment; the primary variable cost driver.
  unit: hours
  aggregation: sum
  dimensions:
  - account
  - dataset
  - plan
- name: points_per_cloud
  description: Point count per point cloud processed; capped per tier (e.g., up to 500,000 on Core).
  unit: points
  aggregation: sum
  dimensions:
  - account
  - dataset
- name: stored_assets
  description: Images, point clouds, and multi-sensor sequences uploaded to Segments.ai-managed storage.
  unit: assets
  aggregation: sum
  dimensions:
  - account
  - dataset
principles:
- name: Visibility
  description: Track labeling-hours consumed per dataset/project against the annual allotment via the metrics dashboard.
- name: Allocation
  description: Map datasets and projects to internal teams/cost centers; unlimited seats means per-project usage, not seats, drives cost.
- name: Optimization
  description: Use prelabeling, active learning, and QA workflows to cut manual labeling-hours; right-size point cloud density; reuse releases instead of re-labeling.
- name: Accountability
  description: Assign owners per dataset; review labeling-hour burn against the annual commitment to avoid overage on Fusion/Enterprise.
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com