Flows Overview
Flows Overview
- Published on Mar 18, 2025
- 1 minute(s) read
With Flows, your instance can have multiple workflows, or flows, which are made of blocks that represent essential parts of the data-extraction process.
In addition to Classification, Identification, and Transcription Blocks, you can work with Hyperscience to add other types of blocks to your flows, such as Input Blocks, Output Blocks, API Blocks, Database Blocks, Flexible Extraction Blocks, Machine Collation Blocks, Custom Code Blocks, and Routing Blocks.
Benefits of Flows
Flows offer the following benefits for your business.
Flexibility
- The flexible and modular nature of blocks lets you decide which steps to include in each of your flows and the order in which those blocks appear in each flow.
- Because blocks contain small units of code, we can develop blocks for specific use cases or industries quickly and easily.
- The ability to have multiple flows allows you to accommodate the processing needs of multiple lines of business.
- The ability to have multiple flows use a single release allows you to process multiple use cases within a single Hyperscience environment. To learn more, see Assigning a Release to a Flow.
- Deploying multiple flows allows you to have multiple live releases at the same time. To learn more, see Managing Flows.
Customizability
- With the help of your Hyperscience representative, you can create flows that are customized to meet the unique needs of your business.
- You can independently configure and manage input and output connections. To learn more, see Managing Connections.
Integrating with your existing systems and processes
- If you have a specific post-processing functionality in mind that you would like to add to your workflow, you can define your own business logic, using Python within Custom Code Blocks. For more information on the current capabilities of Custom Code Blocks, see Flow Blocks.
- With API and Database Blocks, you can connect to data sources in your organization to validate submissions post-Supervision and augment extracted data.