Data retention policy
TickerPal retains Customer Data only while the app is installed and needed to operate the Service. Slack workspace IDs, Slack user IDs, and watchlist ticker symbols are stored so we can answer /ticker requests and send weekday market-close reports. Slash-command text is processed in real time to fulfill the request and is not kept as a query history. Slack OAuth tokens are retained only for the duration of the installation. Public market-data caches are kept only as long as needed to serve quotes. If a workspace uninstalls TickerPal, or a user requests deletion, we delete associated Customer Data within 30 days. See https://tickerpal.com/privacy/ Data archiving and removal policy
TickerPal does not archive Customer Data for secondary use. When a workspace uninstalls TickerPal, or when someone emails support@tickerpal.com to request deletion, we remove associated Customer Data from our systems within 30 days, including Slack installation/token data and watchlist records for that workspace or user. Users can also remove individual tickers in Slack with Unfollow or /ticker unfollow. Website account holders can delete their TickerPal account from account settings. Residual copies in encrypted backups or logs, if any, age out with the normal backup/log cycle.
Data storage policy
TickerPal stores Customer Data in Google Cloud (including Cloud Run and Cloud Firestore) in the United States. Data in transit uses TLS. Access is limited to the systems and credentials needed to run the Slack app and website. We do not sell Customer Data. Ticker symbols from slash commands may be sent to market-data providers to retrieve a quote; workspace and user identifiers are not sent to those providers.
Data center location(s)
United States
Data hosting details
Cloud hosted. The Slack app, API, and website run on Google Cloud (Cloud Run) with Customer Data in Cloud Firestore. Weekday close reports are triggered by Google Cloud Scheduler.
Data hosting company
Google Cloud (Google LLC)
App/service has sub-processors
yes
Guidelines for sub-processors
App/service uses large language models (LLM)
no