Subprocessors
Subprocessors.
StoryHQ relies on a focused set of infrastructure, billing, email, AI, authentication, observability, and background-job providers to operate the service.
Last updated 1 June 2026
01
How subprocessors are used
Subprocessors receive data only as needed for the product features and operations they support. The data shared depends on the feature used: for example, AI providers process uploaded material and derived context when an analysis, notes pass, draft comparison, metadata extraction, or project Q response is requested.
Some providers receive data only when the related feature is used or the provider is configured in the deployment. Provider availability, data locations, and compliance terms may change. StoryHQ will keep this page updated as the operating stack changes.
02
AI processing note
StoryHQ’s core analysis features require AI processing. Uploaded material and derived project context may be sent to model providers to classify material, extract structure, score against rubrics, generate synopsis and notes, compare drafts, generate cast and HOD research lists, and answer project questions.
Current subprocessors
| Provider | Purpose | Data processed |
|---|---|---|
| Vercel | Hosting, serverless functions, deployment, edge/network delivery | Application requests, headers, logs, deployment and runtime data |
| Supabase | Authentication, Postgres database, private storage, realtime, service APIs | Account data, workspace data, uploaded materials, reports, messages, audit events, storage objects |
| Stripe | Checkout, subscriptions, billing portal, invoices, payment method handling | Billing identifiers, customer email, subscription state, payment metadata; full card data is handled by Stripe |
| Brevo | Transactional email and contact-form notifications | Recipient email, sender details, email subject, email body, delivery metadata |
| OpenAI | Structured extraction, scoring, metadata extraction, embeddings, generated materials, and some analysis steps | Uploaded material text, project context, generated intermediate outputs, prompt and response data needed for requested features |
| Anthropic | Long-context creative analysis and synthesis steps | Uploaded material text, project context, generated intermediate outputs, prompt and response data needed for requested features |
| Inngest | Durable background job orchestration for extraction and analysis | Job identifiers, workspace/project/material identifiers, job status, event payload metadata |
| Sentry | Error monitoring and debugging | Error traces, stack traces, user/workspace identifiers where configured, request context, diagnostic metadata |
| PostHog | Product analytics and feature flags where configured | Product events, user/workspace identifiers, device/browser context, feature-flag data |
| Axiom | Structured logs where configured | Application logs, operational metadata, errors, event data |
| OAuth sign-in where the user chooses Google | OAuth identity information such as email and profile identifiers | |
| Apple | OAuth sign-in where the user chooses Apple | OAuth identity information such as email and profile identifiers |
| The Movie Database | Comparable-title lookup and cast/HOD person research where configured | Title, person, credit, and external-ID queries needed to resolve public IMDb links and supporting metadata |