Monetize your accountingfirm's operational data

DataCow partners with accounting firms to help improve AI systems using real-world accounting workflows and operational knowledge. 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 accounting environments.

Companies of many sizes can take part, starting from around 3 to 5 employees, as long as you serve business clients rather than individuals. Beyond size, we look for operationally mature companies with established documentation and complete records: full years rather than fragments, with source documents, workpapers, and review notes kept together so the whole trail of a piece of work is intact. Our current focus is work in financial accounting, transaction accounting, FP&A, tax, and audit. We prioritize US companies, followed by other Western markets.

We are looking for data that reflects how accounting work is actually performed within a company, across financial accounting, transaction accounting, FP&A, tax, and audit. This may include standard operating procedures (SOPs), close and tax workpapers, audit programs, internal knowledge bases, templates, review notes, and other practice artifacts. The most valuable datasets capture real accounting expertise, professional judgment, and repeatable workflows that help AI systems learn how the work is executed in practice.

Protecting client data is a core principle of the program. Personally identifiable information (PII) and client 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 client 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 accounting 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.