Ritual AI Security & Privacy Practices
At Ritual, we want to be transparent with our customers about our products and how we use AI to enhance your experience. Below is an overview of Ritual’s AI functionality and related security and privacy practices.
What is Ritual AI?
Ritual AI is a collection of AI products and features, which currently includes:
- AI Assistant: Helps with generating written content and brainstorming, by leveraging information from across your Ritual workspace and the web.
- Document Generation: Generates text across multiple records in a database simultaneously, based on a pre-configured prompt.
- Custom Domain Models: Leverages advanced machine learning infrastructure to define and deploy organization-specific AI models securely, ensuring tailored AI capabilities within your workspace.
Ritual AI features appear seamlessly in workspaces but leverage technology from several AI subprocessors (listed below).
Data Security
-
No External Training on Customer Data
By default, Ritual does not use your content or personal data to train external or third-party models. Any data you submit via Ritual AI is only used to generate results for your requested tasks and is never provided to external providers for model training. -
Secure Transmission & Limited Retention
When sending data to our AI LLM subprocessors, the data is encrypted in transit (TLS 1.2 or greater). All subprocessors retain data only as necessary—at most 30 days—before deletion. -
Anonymized Usage Data for Platform Improvement
Ritual may use aggregated, de-identified usage data (e.g., how often features are used, performance metrics) to refine and improve our platform’s AI capabilities. This does not include identifiable customer content. -
Custom Domain Models (Opt-In Only)
If your organization elects to develop custom domain models, we offer an opt-in process that uses only your organization’s data. This data remains within Ritual’s secure boundaries and is not shared with other customers or used in third-party model training. The resulting model is accessible exclusively within your organization’s workspace, respecting your internal data policies and ensuring strict organizational boundaries. -
Access-Controlled Data Sharing
Only data the user already has permission to view within the specific workspace is sent to AI LLM subprocessors, ensuring that generated outputs never incorporate content to which the user did not already have access.
Ritual AI Infrastructure
What is a Subprocessor?
A Subprocessor is a third-party engaged by Ritual Mobile, Inc. (and its applicable Affiliates) to process Customer Personal Data in connection with providing our Services.
List of Third-Party Subprocessors
Below is the list of Subprocessors and how we use their services. Click the Subprocessor name for its respective policy or terms.
Infrastructure
We use these Subprocessors for hosting and running our Services. They store and process data within our Service.
| Subprocessor | Purpose of Processing | Location |
|---|---|---|
| AWS | Hosting and storage systems | USA |
| Cloudflare | Web content delivery | USA |
Platform
We use these Subprocessors to help us manage and provide the Service.
| Subprocessor | Purpose of Processing | Location |
|---|---|---|
| AWS – Bedrock | Securely hosting and running generative AI models within the Ritual platform, enabling scalable inference. | – |
| OpenAI | Service provider for large language models and embeddings Note: OpenAI does not train its models on API data. | USA |
| Sentry | Application logging | USA |
| SendGrid | Email delivery | USA |
Customer and Support Services
We use these Subprocessors to offer direct support to you and your team. They are primarily used for communications between Customers and our support teams.
| Subprocessor | Purpose of Processing | Location |
|---|---|---|
| Intercom | Support services | USA |
| Zendesk | Support services | USA |
Business Operations
We use these Subprocessors to manage our business and continue providing you Services. From internal documentation to analytics, these services operate behind the scenes to help us plan and run our business smoothly.
| Subprocessor | Purpose of Processing | Location |
|---|---|---|
| Event logging for analytics | USA | |
| PostHog | Event logging for analytics | USA |
Last updated: July 4, 2024