Ninox API Integration

Ninox is a low-code database platform that supports API access, making it possible to query and update records programmatically from external web applications. This article covers patterns for integrating Ninox as a live data source in automation workflows.

Overview

Ninox functions as a relational database builder — teams use it to create custom internal tools without deep engineering resources. Because it exposes an API, it can serve as a backend data store that web applications query in real time, replacing manual lookup workflows.

The key integration pattern: a web application calls the Ninox API to read or validate records before proceeding with a user-facing action (approval, payment, access control, etc.).

Confirming API Availability

Ninox exposes API access through its settings panel. To verify:

Open the Ninox application
Navigate to the gear/settings icon (top right)
Look for an Integrations or API section

API credentials and endpoint documentation are available from within that panel. Ninox is a SaaS platform, so the API is REST-based and does not require self-hosting.

Common Use Case: Real-Time Balance / Limit Checks

A frequent pattern is using the Ninox API to enforce a business rule at the point of a web form submission — querying a record and comparing a stored value against a threshold before allowing an action to proceed.

Example (WI Masonic Foundation): Lodges apply for matching grants via a website form. Historically, staff manually logged into Ninox to check whether a lodge had remaining annual grant budget ($4,000 cap, May 1–April 30 fiscal year) before approving. The proposed automation queries the Ninox API at form submission time to perform this check automatically. See ^[1] and ^[2].

General Pattern

User submits web form
  → Backend calls Ninox API with lodge/entity identifier
  → API returns current fiscal-year total for that entity
  → Backend compares total + requested amount against limit
  → If within limit: proceed to approval / payment step
  → If over limit: return rejection with explanation

Data Model Considerations

Before building the integration, map the Ninox schema:

Which table holds the entity records? (e.g., Lodges)
Which table holds the transaction/grant records? (e.g., Grants)
How is the fiscal year scoped? Ninox views may apply date filters that are not obvious from the UI — confirm with the person who built the database (often a non-technical internal admin).
Is there a pre-built summary view? Ninox supports computed fields and summary views (e.g., "Lodge Totals") that may already aggregate the values you need, avoiding the need to sum records client-side.

Note: In the WMF case, a "Lodge Totals" view existed in Ninox that showed fiscal-year-to-date grant spend per lodge. Querying this view directly is simpler than summing raw grant records.

Integration Architecture

Read-Only Queries (Approval Checks)

For balance/limit checks, the web application only needs read access:

Authenticate with the Ninox API key
Query the relevant table or view by a known identifier (lodge ID, lodge name, etc.)
Parse the response and apply business logic in the application layer

Write-Back (Recording Approved Transactions)

If the goal is full automation, the integration should also write back to Ninox when a grant is approved and paid, so the running total stays current without manual data entry:

On payment confirmation (e.g., via ^[3]), call the Ninox API to create or update a grant record
This keeps Ninox as the system of record and eliminates the manual logging step

Pairing with Stripe Webhooks

A complete grant automation workflow combines Ninox API reads with Stripe webhook triggers:

Lodge submits application → Ninox API checks balance → auto-approve or reject
Approved lodge receives Stripe payment link
Lodge pays → Stripe fires webhook → application backend:
- Sends notification emails (to fulfillment vendor, finance staff, etc.)
- Writes the approved grant amount back to Ninox

See ^[3] for webhook implementation details.

Stakeholder Mapping Before Building

Ninox databases built by non-technical internal staff often contain implicit logic (custom views, date filters, computed fields) that isn't visible from a brief walkthrough. Before implementing the API integration:

Get the person who built and maintains the Ninox database on a process-mapping call
Walk through the exact fields checked during manual approval
Confirm how fiscal year scoping is implemented in the database
Export a sample dataset to validate field names and data types against what the API returns

This discovery step is a prerequisite for a reliable integration — attempting to build against assumptions about the schema will produce fragile automations.

^[1]
^[2]
^[3]