Integrius SDK
npm package. Python library. CLI. Three ways to build on your governed data platform.
Developer tools for building on top of Integrius. Pull governed data products into your applications, pipelines, and automation, without writing integration plumbing.
Three Ways to Build
Pick the interface that fits your team. All three access the same governed data platform.
npm / Node.js
npm install @integrius/sdkFor TypeScript/JavaScript applications, internal tools, and automation
- Full type-safe API with generated TypeScript types
- Event stream access: subscribe to 34 event types
- Data product queries with pagination, filtering, and projection
Python
pip install integriusFor data engineering teams, ML pipelines, and notebooks
- Pandas-friendly output, returns DataFrames directly
- Jupyter notebook integration
- "The data engineering team writes a script that pulls from the Revenue Analytics data product, joins with internal metrics, and feeds their ML pipeline. 15 lines of code."
CLI
integrius products list --format jsonInfrastructure-as-code teams manage data products via CLI + API
- 25+ commands covering products, sources, events, and lineage
- Zero external dependencies. Node.js built-ins only.
- JSON and table output modes for scripting and humans
This Simple. This Powerful.
No more writing thousands of lines of glue code. Install, connect, build.
import { IntegriusSDK } from '@integrius/sdk';
const integrius = new IntegriusSDK({
apiKey: process.env.INTEGRIUS_API_KEY
});
// Query unified data across all your systems
const customer = await integrius.customers.get('customer_123');
// Returns unified schema - same structure every time
console.log({
id: customer.id,
name: customer.name,
email: customer.email,
orders: customer.orders, // From ERP
support: customer.support, // From CRM
usage: customer.usage // From Analytics DB
});
// One object. Multiple systems. Zero integration code.Built for Integration Work
The SDK that makes complex data integration feel like writing a REST call.
One Schema, Every System
Pull from Salesforce, PostgreSQL, MySQL, APIs, whatever. Output one clean, consistent data structure every time. No more spaghetti code mapping fields.
Build in Days, Not Months
Stop spending 80% of dev time on data plumbing. Build the features that actually matter. Ship customer-facing products in days instead of quarters.
Schema Changes? No Problem.
Upstream systems change all the time. With TOON AI, schema changes don't break your code. We adapt automatically. You keep shipping.
Built on Integrius Core
Get all the power of unified data access with developer-friendly abstractions. The SDK handles complexity. You handle business logic.
AI-Powered Auto-Mapping
TOON understands your data. It maps fields, harmonizes formats, and resolves conflicts automatically. You focus on features, not field mapping.
Governance Built-In
Every SDK call respects RBAC, field-level access controls, and consumer scoping. Your governed data stays governed, with no shadow API paths.
What Teams Are Building
Real use cases. Real teams. Concrete outcomes.
Data Engineering
Pull from Revenue Analytics data product → join with internal Snowflake metrics → feed ML churn model. 15 lines of Python. No ETL pipeline.
Backend Engineering
Build a customer 360 API that fans out to CRM, ERP, and analytics in one typed function call. No coordination with 3 platform teams.
DevOps / Platform
Provision data products from CI/CD pipelines. `integrius products create --config products.yaml` in your deploy script.
Internal Tools
Build a Slack bot that answers "how many active trials do we have?" by querying the Pipeline Forecast data product directly.
ML / AI Teams
Feature store replacement. Instead of duplicating data into a vector DB, query your governed products and enrich embeddings at inference time.
Analytics Engineering
Replace Fivetran + dbt + warehouse with: connect source, define data product, expose API. Done.
Ready to Ship Features, Not Integrations?
Three SDKs. One governed platform. Start building with real data in minutes.