Data retention policy
Outlit stores customer data, including content and related information from Slack conversations customers choose to connect, in cloud services that help us run and protect the product.
We use this data to provide Outlit, keep integrations working, protect the service, and meet legal or contractual requirements. Only authorized people and services can access it. We protect data in transit and at rest, and we do not use customer data to train generalized AI models.
Data may be processed or stored in the United States and other places where our service providers operate. Our current subprocessors are listed at
Data archiving and removal policy
Customers and authorized users can request access, export, correction, or deletion of their information by emailing privacy@outlit.ai. We may ask for information to confirm the requester's identity and authority.
When a customer disconnects Slack, or when we verify a deletion request covering Slack-related data, we delete the covered data within 14 business days. Deleted data may remain temporarily in logs or backups while deletion finishes, within the same 14-business-day period.
Deleting data may cause features that rely on that data to stop working. Where allowed by law and contract, we may anonymize information instead of retaining identifiable data.
Data storage policy
Outlit stores customer data, including content and related information from Slack conversations customers choose to connect, in cloud services that help us run and protect the product.
We use this data to provide Outlit, keep integrations working, protect the service, and meet legal or contractual requirements. Only authorized people and services can access it. We protect data in transit and at rest, and we do not use customer data to train generalized AI models.
Data may be processed or stored in the United States and other places where our service providers operate. Our current subprocessors are listed at https://www.outlit.ai/subprocessors. App/service has sub-processors
yes
Guidelines for sub-processors
App/service uses large language models (LLM)
yes
LLM model(s) used
OpenAI, Gemini, Anthropic
LLM retention settings
Our application is configured to minimize the retention of customer data sent to and processed by our LLM providers (OpenAI, Google Gemini, Anthropic). We do not store customer data for the purpose of training or improving the LLM models of theirs.
LLM data tenancy policy
Our LLM operations are dependent on the data tenancy policies of our underlying large language model providers, including OpenAI, Google Gemini, and Anthropic. Generally, these providers operate globally, and their LLM infrastructure is distributed.
LLM data residency policy
Our application does not store the core models or training data of the LLMs provided by OpenAI, Google Gemini, or Anthropic. For customer data that is processed by these LLMs (e.g., user inputs), we rely on the data residency policies of each respective.