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ML powered Matching in Portal V3 + Workspaces
Field matching in our Portal V3 product is now powered by a machine learning model trained on Flatfile’s knowledge of over 100 million manual matching choices. Now, if matches are not remembered from a previous interaction by that user or organization, global matching kicks in to do the heavy lifting. Our testing shows that over 90% of imports have all headers suggested correctly.
Portal V3 also has a new engine! This change:
improves loading time for all steps of import as well as hooks and validations
allows us to support files of any size (even over 1GB!)
laid the foundation for our improved matching and other upcoming data automation projects - stay tuned!
Flatfile is now hosted in the EU! Contact us if you’re interested in learning more.
Embeds (Portal V3) and Workspaces
Import data table now includes metadata
Validators now support multiple values in arrays
All unique enum values are now shown for matching in Portal, no longer first 1000
We added REST and GraphQL endpoints for adding, updating and deleting rows to Workspaces
Data template JSON editor now shows error if JSON is invalid
Show data previews for excluded fields at Matching
Failed imports will now be retried automatically up to 20 times before the import is canceled
Users will now be notified when trying to add an empty template to an Embed
Improvements to automatic detection of a file’s delimiter
Uniqueness validator no longer highlights the original instance of the duplicate
Improved stability of our data table