Monetize your manufacturingcompany's data

DataCow partners with manufacturing companies to help improve AI systems using real-world sales and CRM, quoting, purchasing, planning, and customer operations workflows. Participating companies receive compensation based on the value of the data provided and may also benefit from improvements tied to the specific use cases they contribute. Data is used to evaluate and improve AI capabilities in realistic enterprise settings.

We look for established manufacturers with repeatable sales and production processes, from specialized contract manufacturers to larger producers. What matters is the depth and continuity of your operational records: sales and CRM activity, customer quotes and orders, purchasing, production planning, quality checks, and delivery. Complete records that show how an order moves from customer inquiry through production and fulfillment are especially valuable. You do not need specialized manufacturing software: work captured in Salesforce, HubSpot, Gmail, Google Sheets, Excel, and other everyday tools can be valuable. We prioritize US companies, followed by other Western markets.

We are looking for data that reflects how work is actually performed across sales and CRM, customer quoting and orders, purchasing, production planning, quality, and delivery. This may include Salesforce or HubSpot records, customer emails, deal notes, quotes, Google Sheets and Excel workbooks, purchase orders, schedules, inspection checklists, standard operating procedures, and review notes. The most valuable datasets connect the request, decisions, actions, and outcome of a workflow. We agree on the scope with you in advance; proprietary designs, formulas, and other information outside that scope are not required.

Protecting customer data is a core principle of the program. Personally identifiable information (PII) and customer identifiers are removed when relevant, access is restricted to a limited number of authorized team members, and your data is processed through isolated pipelines that prevent it from being commingled with other engagements. Data is retained only for agreed periods, you have the opportunity to review representative samples before use, and deletion requests are honored according to the terms of the engagement. In addition, employees with access to data systems use company-managed devices and follow established security controls and training requirements.

All data is handled under strict contractual protections. Before participation, we agree on the approved data scope, security and confidentiality standards, anonymization and redaction requirements, and internal approval processes. Original datasets are retained only for processing purposes. Sensitive information is scrubbed before any downstream use, and all confidential information is removed. Original datasets are deleted after processing. No data is publicly shared, no customer information is exposed, and companies retain ownership of their underlying data.

You do. Companies retain ownership of their underlying data.

After data is shared, it is processed according to the agreed use case and handling requirements. Depending on the nature of the data, personally identifiable information and customer identifiers may be removed and certain datasets may undergo synthetic rewrites that preserve workflow structure while reducing direct ties to original records. Data is retained only for a limited period based on agreed retention policies, and you are given the opportunity to review representative samples before prepared data is used. Upon request or at the end of an engagement, data is deleted according to the agreed retention and deletion terms.

Compensation is determined based on the characteristics and value of the data being contributed. Factors considered include dataset size and volume, workflow complexity, data quality, the sales and manufacturing expertise represented, and the uniqueness of the operational knowledge contained within the dataset. Each partnership is evaluated individually, and compensation is aligned with the overall value and relevance of the data provided.