Sema4.ai
Sema4.ai · Agent platform · US · sema4.ai
services/sema4-ai.yamlVendor data-handling terms
Sema4.ai runs agents against a model the customer chooses. The policy places the training question on that model provider, not on Sema4.ai.
“We do not use your Google data to develop, improve, or train generalized AI and/or ML models. / It is your responsibility to ensure that your chosen LLM's processing of your data is strictly limited to fulfilling your requests and does not involve any other purposes such as training the model or improving it for other users.”
“We retain personal information for as long as necessary to fulfil the purposes for which we collected it, including for the purposes of satisfying any legal, accounting, or reporting requirements, to establish or defend legal claims, or for fraud prevention purposes.”
“We are headquartered in the United States and have service providers in other countries, and your personal information may be transferred to the United States or other locations outside of your state, province, or country where privacy laws may not be as protective as those in your state, province, or country.”
Domains and endpoints
observed means seen in Unseen deployments; vendor-documented means listed by the vendor. Vendors do not publish complete lists.
| Host | Role | Source |
|---|---|---|
| sema4.ai | app | observed |
Assessment
Reasoning: An enterprise agent platform that runs on a model the customer selects. The policy is clear that training exposure depends on that model provider's terms, which is honest but means the answer is only as good as the model contract behind it. US-based vendor; region depends on deployment.
Flags: Training exposure delegated to the customer's chosen LLM provider · US processing for platform data · Assessed 2026-09-16. The assessment is Unseen's; the terms above are the vendor's.
Changelog
- 2026-09-16Documented. Training, retention and transfer terms verified against the Sema4.ai privacy policy.
- 2026-09-15Listed from the Unseen catalogue with observed domains.
Corrections
Pull request on GitHub, or the form below. Changes are reviewed and recorded in the changelog.