The Flow Integration Framework is a powerful data integration engine born out of the need to have a single universal system which can adapt to and consume data from any source, structure or format.
Flow can access and integrate data from any source and consolidate this data for analysis, reporting, and other autonomous tasks.
No matter where your data resides, Flow can connect and adapt it into it's universal generic data. This rapidly accelerates the development of analysis and reporting workflows, letting you focus on implementation and result delivery instead of the bottlenecks of data access.
Flow can be used to interface with any data source, structure or api, synchronize disconnected systems, consolidate data from distributed sources into dashboards and reports, automate analysis workflows, and much more.
Any data integration workflow, no matter how complex, can be developed with no code using Flow. The framework can scale to solve even the most advanced data integration challenges with ease.
Flow's Data Integration Framework allows you to:
Traditionally, the best practice approach to integration was to code fixed connectors or adapters which understand how to parse data coming from a specific source.
While Flow does provide many pre-built adapters to common data formats, it also presents a new generic data approach to integration. Flow's generic data can adapt to any external data source or structure without requiring any knowledge of the data format ahead of time.
This generic data approach allows Flow to connect to tens of thousands of data sources on demand. Flow can connect to any form of API and consume data objects directly into structured tabular data with minimal configuration and zero code.
To see some of the data adapters Flow provides, check out the list below.
Flow operates on a distributed agent architecture which allows for the deployment of powerful automations. Agents are autonomous computing nodes which execute workflows on a schedule or in response to an event. Agents are deployed to wherever data resides, and communicate with the Flow server to orchestrate the coordinated execution of jobs.
Flow enables you to design and develop solutions to the most advanced integration challenges. Once integration workflows are developed - they can be deployed onto autonomous agents for continuous execution on a schedule or in response to an event.
Agent-based Automation allows you to:
Integration workflows are deployed and managed from the cloud. Flow's powerful distributed agent and cloud monitoring technology allows you to monitor all autonomous processes from a central point of control.
Cloud-based Orchestration allows you to:
Flow's high powered configure-not-code workflow editor environment allows you to design rules to transform and cleanse data, and perform any type of advanced calculation as part of the integration workflow.
Flow's integration framework feeds directly into it's data analytics, reporting and dashboards engine. Flow allows you to combine all business critical data sources into consolidated dashboards and reports.
Flow's multidimensional hypercube computing framework allows for the most advanced analytical tasks to be automated as part of integration workflows. Integration workflows can pull data from any number of disconnected sources and unify the data using multidimensional analysis objects.
Flow's HyperCube Integration Framework allows you to:
Flow provides a powerful artificial intelligence and machine learning engine. AI and ML actions can be embedded directly into workflow logic to create intelligent autonomous integrations.
Flow's generic data engine allows the framework to automatically adapt to data from any source, structure or format.
Flow provides many pre-built data adapters. Flow also provides a generic data integration engine which allows the framework to consume any data source or structure not listed below.
Below are some of the out-of-the-box integration interfaces Flow provides: