How-To Do This

How to build Headless SaaS DB

Build a managed, permission-aware SaaS backend for custom web, mobile, desktop, or existing frontends.

Headless SaaS DB is a api-first saas backend pattern. This guide turns the product concept into a buildable first release using BuildWithHQ records, pages, workflows, permissions, integrations, AI, and exact-version packaging.

Define the outcome before the screens

Let a custom frontend use BuildWithHQ records, relationships, workflows, files, AI, and integrations without exposing SQL, provider secrets, tenant infrastructure, or authorization decisions to the client.

1. Create the smallest useful data model

In the Developer Console, create or select the SaaS app and model these as application record types and relationships. The page editor composes React components and validated data bindings, which call the platform APIs for these records.

Relationship rule: Treat client-supplied identifiers as query targets only; derive the builder account, SaaS app, tenant account, user, role, and location from verified server identity.

2. Build the working screens

Start with task-oriented pages instead of a page for every table. The first navigation should contain:

• Your custom customer-facing frontend.
• Internal admin/operations views for the same records.
• Developer Console API-client and integration setup.
• Webhook delivery and correlation-log diagnostics.
• Optional BuildWithHQ pages for back-office workflows.

Use Puck for the normal visual experience. Keep stable block identity when using Monaco advanced JSON mode so future template upgrades can merge safely.

3. Set access before adding automation

• Use app-bound credentials or user sessions appropriate to the caller.
• Enforce tenant, record, field, DataRole, and location scope in the backend.
• Give every client only the operations and fields its use case requires.

User Type menus establish eligible page routes for each audience. They do not grant the records or actions on those pages. The server derives the account, SaaS app, user, DataRole, and location scope from the verified identity on every data request.

4. Add the core workflows

• Authenticated request → identity/context derivation → validation → typed service.
• Typed service → reviewed stored procedure → bounded response.
• State change → workflow/event → signed webhook delivery.
• Inbound event → authenticate → validate → deduplicate → queue/process.
• Failure → safe problem response and correlation evidence.

Make each mutation a narrow, reviewed action with explicit inputs, allowed states, correlation evidence, and an idempotent retry policy where retries are possible. Pages, integrations, and agents all reach the same application service and stored-procedure contract through supported APIs.

5. Connect channels and outside systems

• Start from the generated OpenAPI contract and current REST routes.
• Use externally referenced credentials; never persist raw bearer values in profiles or frontend code.
• Put specialized libraries/services in an appliance with declared endpoints and egress.

Use managed connections, OAuth connectors, inbound endpoints, and webhooks. Put specialized SDKs or private processing behind a declared appliance endpoint; never expose provider credentials to a page.

6. Add AI as a governed layer

Call secured AI capabilities through the API or declared tools. The browser sends the user's request; the server performs authorization, retrieval, context assembly, and governed action handling.

• Keep model/provider credentials server-side.
• Apply the same data permissions used by normal record APIs.
• Return bounded evidence and correlation identifiers.
• Represent material AI mutations as authorized action contracts.

AI and retrieval must apply CanAiReadRecords, tenant, DataRole, field, and location security before context is assembled. Planning and research remain read-only. Customer-facing or material changes use an action suggestion and the configured policy or human approval before execution.

7. Ship one complete vertical slice

Recommended first release: From a small custom frontend, authenticate, list and create one permitted record type, invoke one workflow, receive one signed webhook, and trace the whole exchange by correlation ID.

1. Create the minimum record types and seed representative, non-production data.
2. Build the primary list/queue and one complete detail page.
3. Implement one state-changing workflow and its denial/error states.
4. Add the narrowest useful integration or inbound channel.
5. Add one permission-aware AI read or suggestion only if it improves that workflow.
6. Test as an owner, a normal operator, a restricted user, and an unauthorized user.

8. Validate, package, and operate

• Generate/validate clients against the current OpenAPI document.
• Test cross-app, cross-tenant, field, role, and location denials.
• Test duplicate requests/events and webhook retries.
• Confirm no secrets, SQL details, or internal routes appear in output/logs.

Publish a reviewed exact version as a template when the pattern is reusable. If you sell it, complete the marketplace preparation checks. Template installs are version snapshots; upstream edits must never silently mutate a tenant copy.

Built-in data path: React components and data bindings call authenticated APIs; typed application services execute reviewed stored procedures and return bounded results with audit and correlation evidence.