








































































































.webp)





















ServicePower Optimize is the scheduling and dispatch optimization engine within ServicePower's field service management platform.
Have any questions? We’re here to help You
Connection credits are Makini's billing unit. Each system integration consumes a specific number of credits based on complexity. Systems are divided into three tiers: Tier 1 (simple systems like cloud CMMS), Tier 2 (mid-complexity ERP systems), and Tier 3 (complex systems like SAP). On-premises installations require double the credits of their cloud equivalents. For example, a cloud SAP S4/HANA connection might use 4 credits, while an on-premises SAP ECC installation uses 8 credits. Connection credits are consumed when you establish a connection and are returned to your pool when you disconnect. This allows flexible allocation across customers—you're not locked into specific connections.
Makini's API supports date filtering on most endpoints using query parameters. You can filter by creation date, modification date, or entity-specific date fields like order date or delivery date. Common patterns include modified_after=2024-01-01 to retrieve records updated since a specific date, or relative timestamps like modified_after=2024-01-01T00:00:00Z. For optimal performance, use incremental data retrieval patterns rather than repeatedly fetching all records. The sync status endpoint provides the last sync timestamp, which you can use as the modified_after value for your next query. This approach minimizes data transfer and API load while ensuring you capture all changes.
Yes, through Makini Flows, which includes connectors for popular databases including Snowflake, PostgreSQL, MySQL, MongoDB, and others. This enables workflows that synchronize data between industrial systems and your data warehouse or analytics platforms. For example, you can sync purchase orders from SAP to Snowflake for analytics, or use database queries to drive integration logic. Database integrations use the same workflow builder as other integrations, making it easy to combine industrial system data with database operations. For direct database-to-database syncing, we can help design optimized workflows. Database connections are treated as custom integrations and may require additional workflow development.
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.
