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Makini maintains a comprehensive data model built from analyzing thousands of industrial systems. When data flows through Makini, we automatically transform it from the source system's format into our standardized structure. For example, purchase orders from SAP, NetSuite, and Dynamics all return with consistent field names, data types, and structures. This normalization happens in real-time as data passes through the API. You also have access to raw data if needed for specific use cases. The unified model covers common entities like purchase orders, work orders, inventory items, vendors, and assets, with extensive field coverage across systems.
The `RATE_LIMIT_EXCEEDED` error indicates you've exceeded the API rate limit for the connection or account. Rate limits are typically set per connection and per time window (usually per minute). When you hit a rate limit, the response includes a `Retry-After` header indicating when you can retry the request. Implement exponential backoff in your retry logic to avoid immediately hitting the limit again. If you consistently hit rate limits, review your API usage patterns—you may be making unnecessary requests, polling too frequently, or could benefit from webhook-based synchronization. For legitimate high-volume needs, contact us to discuss increasing your rate limits.
Makini uses cursor-based pagination for retrieving large datasets. API responses include a `next_cursor` field when additional results are available. To retrieve the next page, include the cursor value in your next request: `GET /api/v1/purchase-orders?cursor=CURSOR_VALUE`. Cursor-based pagination is more reliable than offset-based pagination because it handles data changes between requests—if records are added or deleted while you're paginating, you won't miss records or see duplicates. Page size is configurable up to a maximum limit (typically 100-500 records per page depending on entity type). For optimal performance, use the largest page size your application can handle efficiently. The API response also includes total count when available from the source system.
Based on our market data, building industrial integrations in-house typically costs $50,000-$150,000+ per integration and takes 2-24 months depending on complexity. Maintenance requires dedicated resources—roughly one full-time person per three integrations. Makini transforms these economics: integrations go live in 1-6 weeks, costs are predictable OPEX rather than large upfront CAPEX, and maintenance is included. You gain access to 2,000+ integrations instead of building them one at a time. Our team has six years of specialization in industrial integrations, meaning we've solved problems you haven't encountered yet. For product companies, Makini allows faster time to market and frees engineering resources to focus on your core product rather than building and maintaining integration infrastructure.
