An open marketplace where you decide if AI can train on your data vs a program built to buy it for training
Companies like micro1, Mercor, Prism (Labelbox), and Protege license company data to train AI models. Spartera is an open marketplace for analytics and data feeds, where every product carries a seller-controlled AI training setting that is off unless the seller turns it on. One sells a copy of how your business works. The other earns from your data every time it's bought, on your terms.
A new category of AI data companies now pays businesses to license their operational data. micro1, Mercor, Prism by Labelbox, and Protege source SOPs, knowledge bases, CRM records, tickets, and workflow histories, then anonymize and package them so AI labs can train and evaluate models. Training is the whole point of the transaction. Spartera works differently. It is an open marketplace where you publish analytics and data feeds computed from your own warehouse, and buyers, including analysts, companies, and AI agents, purchase them on demand. Spartera doesn't acquire your data: buyers license each purchase from you, and Spartera runs the marketplace. Every product states whether it may be used to train AI models, and that setting belongs to you. Unless you turn it on, the listing says "Not for AI training," and that statement is a term of every buyer's license. These two models are not mutually exclusive: many companies can license documents to a training-data partner and sell structured analytics through Spartera.
Quick decision guide to help you choose the right solution
Side-by-side comparison of key features and capabilities
What makes these solutions different
Every Spartera product has an AI training setting: permitted or not permitted. You can set it once as an account-wide default for current and future products, then override it on individual products. Training-data licensing works the other way around: training is the reason the data is being bought.
If you never touch the setting, your listings say "Not for AI training." Turning training on is a deliberate act: you confirm that you hold the rights to grant it, including over any third-party data in the product, and Spartera records who confirmed it and when.
Buyers may always analyze what they purchase with AI tools, including agents that query your products for answers. The setting governs one thing: whether purchased data may be used to train, fine-tune, or improve a model. That distinction lets you sell to the AI economy without donating your data to someone's model.
Each listing shows its AI training setting before purchase, and the buyer receives it as a term of the license. Spartera records the setting with every purchase, so it's always clear what a given buyer was granted. If you change the setting later, the change applies to future purchases.
With training-data licensing, you're paid for the data you deliver, and earning more means handing over more. On Spartera, the same product can sell to many buyers, and buyers come back when your data updates or they need different filters, while nothing more leaves your systems. Licensing can offer committed money up front; Spartera revenue follows buyer demand, with the standard 80% seller share on each sale.
These models solve different problems. Operational documents like SOPs and playbooks suit a training-data licensing deal. Structured metrics and records suit Spartera. Many companies can do both. Just check that no licensing deal grants exclusivity over data you also want to sell.
When each solution shines in practice
A company whose business is its data wants new revenue without letting buyers build a model that replaces it. On Spartera, it publishes analytics and feeds with AI training not permitted, sells to analysts and AI agents on demand, and keeps its raw tables in its own warehouse.
A seller is happy for AI companies to train on some products but not others. It turns training on for an aggregated benchmark product and leaves it off for its detailed feeds. Each listing shows the difference, and each purchase records the terms that applied.
A company with frequently updated metrics prefers income every time its data is used. Spartera bills each purchase and pays the seller its share, so revenue tracks demand for its data rather than the size of the datasets it hands over.
A services company has years of SOPs, support tickets, and project histories but little structured data to sell. A training-data licensing partner can anonymize and package that operational knowledge for AI labs, which isn't something a structured analytics marketplace is built to sell.
A business actively wants its workflows to shape how AI models learn and prefers a single negotiated deal. Training-data licensing is designed exactly for that.
License anonymized operational documents to a training-data partner, and publish your structured metrics on Spartera with AI training not permitted. You earn from both while keeping control of your core data. Confirm that the licensing agreement doesn't grant exclusivity over data you list on Spartera.
Common questions about this comparison
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