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Integration timelines vary by complexity. For standard implementations with no customizations, connections can be live within 1-2 weeks. This includes authentication setup and basic workflow configuration. For implementations requiring custom workflows or specific business logic, timelines typically range from 2-6 weeks depending on the scope. Complex enterprise deployments with multiple systems and custom requirements may take 6-10 weeks. These timelines are significantly shorter than traditional integration projects, which often take 2-24 months.
500-level errors indicate issues on Makini's side or with the connected system. These are typically temporary and retrying the request after a brief delay often succeeds. Implement exponential backoff for retries—wait a few seconds, then progressively longer intervals. If errors persist beyond a few retries, check the Makini status page for service disruptions. The error may also stem from the connected system experiencing issues rather than Makini itself. For persistent 500 errors, contact support with the request ID from the error response. Include details about when the error started, which operations are affected, and which connections are impacted. Our support team can quickly identify whether the issue is systemic or connection-specific.
Write operation limitations vary by system. Common limitations include: field-level restrictions (some fields may be read-only), business rule validation (orders may require certain fields or valid vendor codes), permission requirements (the connected account needs specific permissions), timing restrictions (some systems prevent modifications after certain workflow states), and rate limits on write operations. Custom fields in target systems may not be writable through standard APIs. Some systems have transactional requirements—for example, purchase order line items must be created in the same transaction as the order header. During implementation, we identify write operation limitations for your specific use cases and design workflows that work within those constraints.
Yes, Makini supports multi-region deployments for customers requiring data residency in specific regions or needing high availability across geographies. Each region runs an independent instance of Makini with its own infrastructure, ensuring data remains within the specified region. Multi-region deployments are most common for self-hosted installations where customers want instances in multiple AWS regions or data centers. For cloud deployments, we can discuss region-specific hosting based on your requirements. Multi-region support ensures compliance with data localization regulations and provides geographic redundancy for mission-critical integrations.
