Our developers have been working hard to bring Artificial Intelligence into FME in various ways, helping you to leverage the power of AI in data integration workflows. We’re excited to share that we’ve made it easy for users to stay up-to-date with rapidly evolving AI services and confidently integrate the power of AI into FME.
We are working on 3 ways to use AI in FME:
- AI Assist for FME Workbench, designed to help you author workflows more effectively and solve problems faster.
- AI Connectors in FME Hub, a growing collection of transformers to integrate any AI service into your data integration workflows and gain better insights (e.g. OpenAIChatGPTConnector).
- AI Insights for FME Flow administrators, helping to increase reliability and stability across the enterprise by identifying problems before they happen.
Today, I want to highlight the first one, which is currently in our betas as a Tech Preview: AI Assist.
- Watch our AI webinar to see demos of all 3 of the above use cases
What does FME’s AI Assist do?
You’ll see a new button available in various FME Workbench dialogs:
It helps you create SQL queries, regular expressions (RegEx), or Python code in FME Workbench parameters and dialogs that accept these types of values.
For example, in transformers that support Python (e.g. PythonCaller), you can use AI Assist to generate Python from a description or existing code and then refine, explain, or add comments to it. In parameters that support regular expressions (e.g. StringReplacer) or SQL queries (e.g. InlineQuerier), you can input a description in plain English, and AI Assist will generate the expression/query and an explanation of the result.
See the AI Assist documentation for detailed information on how to use this functionality.
Have you tried it? What else would you like AI to help you with? Let us know by sharing your thoughts and feedback in the FME Community!
