
When this happens...
Job Completed
New Client
New Job
Job Queued
New Form Response

Automatically do this!
Enable Integrations or automations with these events of ServiceM8 and TimescaleDB
Triggers when a Job's status changes to Completed.
Triggers when a new Client is created.
Triggers when a new job is created.
Triggers when a Job is assigned to a Queue.
Triggers when a Form is completed. Requires the Forms add-on to be enabled in your ServiceM8 account.
Create a new client
Get an existing client list
Create a new Job.
List all the jobs.
Create a new job queue.
List all attachments
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Workflow automation is the process of using technology to execute repetitive tasks with minimal human intervention, creating a seamless flow of activities.
To start, connect both your ServiceM8 and TimescaleDB accounts to viaSocket. Once connected, you can set up a workflow where an event in ServiceM8 triggers actions in TimescaleDB (or vice versa).
Absolutely. You can customize how ServiceM8 data is recorded in TimescaleDB. This includes choosing which data fields go into which fields of TimescaleDB, setting up custom formats, and filtering out unwanted information.
The data sync between ServiceM8 and TimescaleDB typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between ServiceM8 and TimescaleDB. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
ServiceM8 is a field service management software that helps businesses manage jobs, schedule work, and streamline operations. It is designed to assist service-based businesses in improving efficiency and customer satisfaction.
Learn MoreTimescaleDB is a powerful time-series database designed for fast ingest and complex queries, making it ideal for handling time-series data efficiently. It extends PostgreSQL, providing scalability and performance enhancements specifically for time-series workloads.
Learn More