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Training-data company

Labelbox Prism

Prism, operated by Labelbox, acquires operational data and work documents from companies and contributors to supply frontier AI developers. Its page publishes deals from around $50,000 for smaller targeted datasets to more than $1 million for large enterprise partnerships, pays an upfront licensing fee at signing plus a revenue share on downstream use, and makes licenses exclusive by default.

Facts checked against Labelbox Prism's own pages in November 2026. Visit Labelbox Prism

At a glance

What it buys
Work documents (coding sessions, research traces, financial modeling) and operational data from systems such as Salesforce, Jira and SAP
Published payout
From around $50,000 (smaller targeted datasets) to more than $1 million (large enterprise partnerships)
Size requirement
Not published. Prefers high-volume B2C companies for support logs
Exclusivity
Exclusive by default, tailored to scope, sensitivity and strategic value
Fee to seller
Not published. Scoping is free and non-binding
Payment timing
Upfront fee at signing plus revenue share. Prism says first call to first wire takes under 21 days

Key takeaways

  • Labelbox Prism is a training-data company.
  • What it buys: Work documents (coding sessions, research traces, financial modeling) and operational data from systems such as Salesforce, Jira and SAP.
  • Published payout: From around $50,000 (smaller targeted datasets) to more than $1 million (large enterprise partnerships).
  • Size requirement: Not published. Prefers high-volume B2C companies for support logs.
  • Exclusivity: Exclusive by default, tailored to scope, sensitivity and strategic value.
  • Facts checked on Labelbox Prism's own pages in November 2026.

What does Labelbox Prism buy?

Labelbox Prism buys two kinds of data: work documents such as coding sessions, research traces and financial modeling, and operational data from systems such as Salesforce, Jira and SAP. Categories it lists with buyer interest include financial reasoning traces, cross-system interaction data, multimodal medical records, code generation and edit traces, and consented likeness and voice.

Some categories carry conditions. Medical records need IRB approval or qualified de-identification, and likeness and voice data need explicit, timestamped consent.

How much does Labelbox Prism pay?

Labelbox Prism publishes a range from around $50,000 for smaller targeted datasets to more than $1 million for large enterprise partnerships, and says compensation varies by project. You receive an upfront licensing fee at signing plus a revenue share on downstream use. The page does not say when revenue share payments are made.

Licenses are exclusive by default. An exclusive license with a revenue share ties your future income to one buyer's sales, so read our guide to exclusive and non-exclusive licenses first.

How long does a Labelbox Prism deal take?

Labelbox Prism published process, checked November 2026
StepWhat happensStated time
ScopeIntake form and call, systems mapped, written quoteAbout 10 minutes, quote within 48 hours
ProcessData prepared1 to 3 days
LicenseLicense agreed and signed5 to 10 days

Prism says data is filtered, anonymized, aggregated or permissioned before use, with personal information removed on export. It lists encryption in transit and at rest with customer-managed keys, regional residency guarantees and read-only connectors.

Who is Labelbox Prism a good fit for?

Labelbox Prism suits companies with reasoning-rich work records, such as software companies and financial services firms, that are comfortable with exclusivity in return for an upfront fee and ongoing revenue.

Comparing buyers?

Published payouts are ceilings, not quotes. We can put your records in front of several vetted buyers and compare offers on the same terms. Get a free valuation.

Sources

  1. Prism, Labelbox, accessed November 2026

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Labelbox Prism is listed for reference. We are independent and this page is not an endorsement. If anything here is out of date, email hello@sellmydatatoai.net and we will correct it.