You can now select data from dropdowns in your document.
For example, let's say you wanted to add the currency code to a document. Simply upload a csv file with th 3 digit currency codes and create a select from dropdown label, choose your database and column and you're all good to go!
We've finally released this feature! You can now go ahead and upload CSV files in your external integrations and use that to pull/enrich information on your document.
Let's say you want to pull the Vendor GL code based on the vendor name in your invoice. All you need to do is upload the CSV file, use the derive fields from database post processing and get the vendor code into Nanonets!
We've recently added post processing and formatting options to your tables as well!
Head over to the labels section of your model and go to the Table headers section to set these up! Example link: https://app.nanonets.com/#/ocr/labels/MY_MODEL_ID?label_type=table_column
These post processing options will apply to each row in the extracted table in your document
The Extract data section of your model as well as the Prediction APIs now supports rotation of the documents you've uploaded.
For eg: If you've uploaded an document which is originally rotated by 90 degrees, the orientation will get automatically corrected and displayed on Nanonets
Approvals such as 2 way matching and date validations can now be setup for line items as welll
You can now directly integrate your MS SQL databases
You can head over to the External Integrations Tab and configure your MS SQL database. Once this is done, the data extracted from the files that you upload to Nanonets will directly flow into your MS SQL database. This includes labels as well as line items.
You can now select the exact page in the pdf you want to process through your model settings section.
For eg: Let's say you've uploaded a 5 page pdf form and the data that you're looking to extract is only on page 2, you can specify this in your model settings. This should reduce your API usage as well an speed up the processing time
Searching for files on the annotate section of your model is now much easier. The search supports filters as well as full text search on the text in the document.
You can add filters on the labels as well as find files where the annotation does not exist.
You can now add your own post processing and validations to your model via python code.
You can head over to the Manage Labels section of your model and get this done. It is available as the "Python Script" option under post processing and validations
This is a significantly powerful feature that lets you modify or validate the model's outputs exactly as per your specification
You can now add multiple conditions to match the data derived from a document in a database.
