Bitskout - supercharging monday.com with no-code AI

A small update - Bitskout has been approved for monday.com marketplace apps. You can now install it from the marketplace.

Feel free to reach out.
Ilia

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We’ve just release a major update adding new recipe for comparison workflows. Also now data extraction supports “Date” field so you can extract dates from documents and put them into task’s Date column.

Some of our customers do like this:

  • factory uses a form to upload the target documentation
  • run comparison on two files (shipping documentation or similar)
  • trigger Date extraction from a source and a target.
  • once it is done, run a date check (shipping dates should be the same or shipping date less max 3 days from packaging date for fresh products and etc.)

Feel free to reach out for details.
Ilia
Bitskout

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Happy Easter everyone!

We’ve just released our new feature that allows mapping the results of A.I. model execution to labels in your boards. This will facilitate more automations because now you can trigger automations based on that mapping.

We’ve recorded an example where we use that technique to detect document types and select appropriate labels:

Cheers,
Ilia, Bitskout

Hey there!

Another example of advanced workflow with help of Integromat, monday.com and Bitskout that we’ve created for one of the clients. Using that workflow allowed the client to decouple work completion and reporting - once the teammate complete the task, the document was uploaded to his folder and Bitskout and Integromat took care of everything else. This allowed to remove a lot of unnecessary processes and simplified the work for the team.

The process is as follows: once the file is uploaded to a folder on Dropbox, we use Integromat to detect the new file. Then once we detect the file, we create a new task in monday.com with a file URL. The new task triggers Bitskout no-code A.I. workflow that checks what is the document and assigns the label. Once we know the document type via label we trigger a monday.com automation to move the file to a new board where, again using Bitskout no-code A.I., we extract information from the document.

The example is using supply chain documentation (bill of lading) detection but obviously it can be used with different documents.

Feel free to ask about the details.
Cheers,
Ilia

Today a small update - the barcode detection is now available under Image Analysis.

Cheers,
Ilia

Hey there!

Another use case that shows the power of monday.com combined with no-code A.I. - automating creation of Knowledge Base with help of monday. The key item here is the creation of a board and a form where all tasks are coming in. Bitskout A.I. is used to automatically generate keywords, analyze images and create machine-based taxonomy for your request that would allow you to classify your content.

Forms can be used as a QR code printouts.

Cheers,
Ilia

Happy Monday everyone!

Another demo and this time about sub-items. In this video we show how you extract a table from a PDF document and convert its rows into sub-items of a Monday task.

This functionality is really useful when you have a table that is populated based on user action (some kind of an order of something) or selection (a set of options). And also it allows you to parse tables coming from a document delivered by a partner - for instance, invoices or receipts where you want to have itemised list be available as sub-item of a main item.

Table extraction functionality is available right now.
Cheers,
Ilia

Hey!

I’ve created a bit more enhanced example where I used JotForm configurable list field to make a dynamic choice for the user to add items to the table and then saved the submission to Dropbox. This way I’ve managed to convert JotForm submission into monday.com task with sub-items and extract information about the order to the same task:

Feel free to ask any questions.

Cheers,
Ilia

Hey everyone!

We’ve created a small guide which describes how we’ve created the supply chain document detector in monday. We’ve used the same trick with another client detect incoming email RFIs from different contractor and moving them to respective boards and then extract information to monday fields.

You can use the same trick to track any documents you’d like.

Also, here is a blog post:

Cheers,
Ilia