Document Extraction package updates
- Updated: 2025/04/22
Document Extraction package updates
Review the updates in released versions of the Document Extraction packagesuch as new and enhanced features as well as fixes and limitations. The page also lists the release dates of each version, and the compatible Control Room and Bot Agent versions.
Versions summary
The following table lists the versions of Document Extraction package released either with an Automation 360 release or as a package-only release (in descending order of release dates). Click the version link for information about updates in that package version.Version | Release date | Release type | Bot Agent version | Control Room build |
---|---|---|---|---|
3.36.10 | 17 March 2025 | Package-only; post Automation 360 v.36 (Sandbox) release | 21.252 or later | 19223 or later |
3.36.7 | 5 March 2025 | With Automation 360 v.36 (Sandbox) release | 21.252 or later | 19223 or later |
3.35.14 | 15 January 2025 | Package-only; post Automation 360 v.35 release | 21.252 or later | 19223 or later |
3.35.7 | 26 November 2024 | With Automation 360 v.35 (Sandbox) release | 21.252 or later | 19223 or later |
3.34.7 | 27 September 2024 | With Automation 360 v.34 (Sandbox) release | 21.252 or later | 19223 or later |
3.33.18 | 15 July 2024 | Package-only; post Automation 360 v.33 release | 21.252 or later | 19223 or later |
3.33.13 | 14 June 2024 | Package-only; post Automation 360 v.32 release | 21.252 or later | 19223 or later |
3.33.11 | 26 June 2024 | With Automation 360 v.33 (On-Premises) release | 21.252 or later | 19223 or later |
3.32.26 | 18 April 2024 | Package-only; post Automation 360 v.32 release | 21.252 or later | 19223 or later |
3.32.23 | 5 April 2024 | With Automation 360 v.32 (On-Premises) release | 21.252 or later | 19223 or later |
3.32.22 | 21 March 2024 | With Automation 360 v.32 (Sandbox) release | 21.252 or later | 19223 or later |
3.31.22 | 26 January 2024 | Package-only; post Automation 360 v.31 release | 21.252 or later | 19223 or later |
3.31.17 | 22 December 2023 | Package-only; post Automation 360 v.31 (Sandbox) release | 21.252 or later | 19223 or later |
3.31.16 | 6 December 2023 | With Automation 360 v.31 (Sandbox) release | 21.252 or later | 19223 or later |
3.31.15 | 28 November 2023 | With Automation 360 v.30 release | 21.252 or later | 19223 or later |
3.31.13 | 16 November 2023 | Package-only; post Automation 360 v.30 release | 21.252 or later | 19223 or later |
3.30.24 | 21 September 2023 | Package-only; post Automation 360 v.30 (Sandbox) release | 21.252 or later | 19223 or later |
3.30.22 | 6 September 2023 | With Automation 360 v.30 (Sandbox) release | 21.252 or later | 19223 or later |
3.30.21 | 21 August 2023 | Package-only; post Automation 360 v.29 | 21.98 or later | 15345 or later |
3.30.19 | 16 August 2023 | Package-only; post Automation 360 v.29 | 21.98 or later | 15345 or later |
3.29.17 | 17 July 2023 | Package-only; post Automation 360 v.29 release | 21.98 or later | 15345 or later |
3.29.14 | 6 June 2023 | With Automation 360 v.29 (Sandbox) release | 21.98 or later | 15345 or later |
- To download an individual package (updated in an Automation 360 release where you want only the package), use this
URL:
https://aai-artifacts.my.automationanywhere.digital/packages/<package-file-name>-<version.number>.jar
- For Document Extraction
package, the naming convention is:
bot-command-iqbot-extraction360-<version-number>-full.jar
For example,
bot-command-iqbot-extraction360-3.31.22-full.jar
For detailed steps on downloading a package and manually adding it to the Control Room, see Add packages to the Control Room.
3.36.10
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
What's new |
---|
Advanced data extraction using prompt
tag The @AdvancedExtraction prompt tag is introduced to use advanced vision-powered generative AI models for better data extraction. You must add this tag at the end of a single table field per table or in the table prompt to use vision-powered generative AI models for data extraction. |
Limitations |
---|
The @GenAIVision prompt tag is not supported for form fields when using the Anthropic Claude vision-powered generative AI models. |
Bring your own license (BYOL) is not supported for the OpenAI o1-mini model. |
3.36.7
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
What's new |
---|
Support for test mode and PDFBox
features Document Extraction package supports test mode and PDFBox features. Test learning instances | Create a learning instance in Document Automation |
Fixes |
---|
When special characters (=, -, @, +, <, > ,) are used in field names, special characters in the field names will be enclosed in single quotes (' ') in the output CSV file. |
3.35.14
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
What's new |
---|
Data extraction using vision-powered generative AI models Vision-powered generative AI models are integrated in Document Automation to process documents with visually-complex structures such as recognizing checkboxes and detect signatures. Vision-powered generative AI models provide the following benefits:
Vision-powered generative AI data extraction | Using prompt tags in generative AI prompts |
What's changed |
---|
Improved accuracy of data extraction
(Service Cloud Case ID: 02113080) The accuracy of extracting data using the Extract data action is improved when you use vision-powered generative AI models. See Vision-powered generative AI data extraction. |
Improved
table extraction model (Service Cloud Case ID: 02159567, 02154057,
02145073, 02163032, 02151987, 02175105) The table extraction model is updated to process documents that have complex headers in tables and to extract data from tables from all pages. |
Fixes |
---|
You can now extract data using newer versions
of the Microsoft OpenAI GPT-4o model. Previously, data extraction failed when using older models in certain scenarios. |
You can now use MS OpenAI bring your own
license (BYOL) to extract data without getting an error. Previously, an error was displayed in certain scenarios. Service Cloud Case ID: 02177260 |
Data extraction will now work in learning
instances that are using a generative AI provider
and the fields are configured with the Search query for
Generative Al model option to return the response in the JSON
format. Previously, data extraction might have failed or returned empty values for such fields. |
You can now extract value from stacked data
using prompt tags. See Using prompt tags in generative AI prompts. Previously, the correct value was not extracted in certain scenarios. |
Data extracted from fields will no longer
include a quote prefix. Previously, some extracted data included a quote prefix. |
When you process documents using migrated
learning instances and if the documents are moved to the validator,
validation feedback can now overwrite the field values extracted by the
default engine. Previously, validation feedback could not overwrite the field values in such a scenario. |
3.35.7
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
What's changed |
---|
Improved table extraction model (Service
Cloud Case ID: 02141734) The table extraction model is updated to process documents that have complex headers in tables. |
Fixes |
---|
You can now extract data from table headers
after providing validation feedback. Previously, only partial data was extracted in certain scenarios. Service Cloud Case ID: 02155613 |
You can now process documents for extraction
data without encountering storage-related error. Previously, storage-related error was displayed when processing certain documents. Service Cloud Case ID: 02141163, 02132605 |
Fixed security vulnerability issues. For more information, click the release download link and view the Security & Compliance reports at A-People Downloads page (Login required). |
3.34.7
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
What's changed |
---|
Improved table
extraction model The table extraction model is updated to enhance the end-of-table indicator option. Service Cloud Case ID: 02145073, 02154694, 02160765 |
Fixes |
---|
When you create a learning instance with the document type set to Unstructured document and the language set to Swedish, the Document Extraction successfully extracts data from the Unstructured document type for the Swedish language. |
You can now provide queries in the
Search query for generative AI model option and
extract data successfully from packing list documents without seeing an
error. Previously, an error was displayed when you provided certain queries in such a scenario. Service Cloud Case ID: 02154341, 02154706, 02173044 |
Fixed security vulnerability issues. For more information, click the release download link and view the Security & Compliance reports at A-People Downloads page (Login required). |
3.33.18
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
What's new |
---|
Out-of-box Anthropic integration You can now use Anthropic generative AI provider directly without any additional configuration. |
What's changed |
---|
Improved table extraction
model The table extraction model is updated to improve data extraction for tables spanning across multiple pages for unstructured document types. |
Fix |
---|
When extracting data using a generative AI provider, fields will return appropriate value if the response is requested in JSON format within the search query. Previously, specific fields were returning empty value in such a scenario. |
3.33.13
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
What's changed |
---|
Improved table extraction model (Service Cloud Case ID:
02122434) The table extraction model is updated to improve the table structure extraction and error handling. |
Fixes |
---|
You can now provide validation feedback in
the standard vendor_name form field in a learning
instance to successfully extract vendor names. Previously, you encountered an error in such a scenario. Service Cloud Case ID: 02124772, 02122434, 02126627, 02129868, 02132605 |
For documents that contain multiple pages
and tables, the primary column and end-of-table indicator fields for all
the tables in the advanced training settings of the validator are updated
appropriately after providing validation feedback. Previously, the primary column and end-of-table indicator fields were not updated for all tables. |
Validation feedback now works for multi-tables when you process documents that contain multi-tables with learning instances. |
Limitation |
---|
Data extraction will fail in the following
scenario:
|
3.33.11
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
Fixes |
---|
You can now process documents using a
learning instance when:
Previously, data extraction failed in such a scenario. |
3.32.26
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
Fixes |
---|
When you process a document with Google Document AI, the extraction bot now executes successfully for Portuguese language and sends the document to validator. |
When you process a document with handwriting or signature objects, these objects are now included in the final output JSON file. Previously, due to high confidence threshold set for signatures, handwriting or signature objects were not included in the final output JSON file. |
When you process a document using Google Custom Document Extractor (CDE) with bring your own key (BYOK) setup and the corresponding processor is using foundational model, the document processing no longer fails due to transformational failure. |
With improved table structure model
specifically for complex tables column detection, you can now get the
more accurate extraction results. Service Cloud Case ID: 02110860 |
For learning instances bridged from IQ Bot to Document Automation, when validation feedback is enabled and validation feedback is applied, and user processes the next document, the data from all the pages now extracted successfully without any merged rows. |
3.32.23
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
Fixes |
---|
Fixed the vulnerabilities reported in the security scan. |
3.32.22
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
Fixes |
---|
With improved document table detection model
that is adding End of Table indicator, you can now
extract table data from all the pages for the selected language. Thus, it
reduces missing tables and last rows extraction issues from
pages. Service Cloud Case ID: 02065073 |
With improved table extraction, unstructured tables no longer show the junk values and now extracts the table data successfully. |
Users can now save the validation feedback in
their Document Automation environment when the proxy is enabled
in the Bot Agent machine. Service Cloud Case ID: 02092484 |
With Google Vision OCR and proxy enabled, the document extraction no longer fails for unstructured document and does not show an error message. Service Cloud Case ID: 02104409 |
3.31.22
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
Fixes |
---|
After adding validation feedback to the
learning instance, the document extraction no longer fails with an error
message. Previously, the document extraction was failing when validation check box was selected. |
After adding validation feedback to the
learning instance, the feedback is saved for all the tables across all
the pages in document and data is extracted correctly from all the
pages. Previously, the feedback was not saved for all the pages. Service Cloud Case ID: 01995135, 02093575, 02093389 |
After adding the validation feedback, if the
table IDs are matching, data from all the tables from every page is now
extracted and showing up in the validator. Previously, in such cases, some pages were skipped and data was not showing in validator from all the pages. |
When you apply the advanced training
settings, you need to swap columns and all the column values need to be
mapped correctly. As a result, data is extracted correctly in separate
columns. You can select either to re-map all column cells or remove all
other incorrect cell rows while keeping the first two rows intact. There
should be no incorrect cells in the column and all column cells should
have the correct values. Previously, in such cases, the data from two columns was extracted in a single column. |
You can now extract the table fields values
in correct order and the multi-row extraction issue no longer persists.
Also, you can use the End of table indicator
feature to extract multi-line after applying feedback data when there is
only one row in table. Note: For single row tables,
the best practice is to use the End of table
indicator feature. Otherwise, in specific scenarios
extraction might be partial. Service Cloud Case ID: 02091013 |
After training a document, when user
processes the same document with Google Vision OCR, the feedback
gets saved and extracts the required data. Previously, in such cases, you were not able to process a specific type of document and each time required to validate the document manually. Service Cloud Case ID: 02098682 |
3.31.17
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
Fixes |
---|
With Google Vision OCR, you can now
process the documents successfully without a Google Document AI
license. Also, it does not generate an error message. Previously, it requested a Google Document AI license to process the documents and generated error while extracting documents. As a result, you were not able to extract documents with Google Vision OCR. Service Cloud Case ID: 02097428, 02096992, 02097798, 02097157, 02098378, 02098563, 02094573 |
3.31.16
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
Fixes |
---|
When users create a learning instance with
Google Document AI (BYOK) and authenticated proxy, the
document extraction no longer fails for more than 10 pages
document. Previously, in such cases, extraction failed with an error message and users were not able to process the documents. |
3.31.15
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
Fixes |
---|
If Document rules contain multiple conditions using the AND operator with (or without) a group, an appropriate error message is now displayed. Also, the corresponding action is now applied on the fields. |
3.31.13
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
What's changed |
---|
With improved extraction of unstructured documents in
Document Automation, you can:
|
Fixes |
---|
With improved table extraction using the
ABBYY OCR engine, heuristic feedback is now working properly.
Service Cloud Case ID: 01995901 |
When a user extracts the table data from a
PDF file where table is expanded to multiple pages, the data from all the
pages extracted successfully after applying the heuristic feedback.
Previously, users were not able to extract data from the second page of the PDF file where table is expanded to multiple pages. Service Cloud Case ID: 01996536 |
Starting the extraction from first
page for all the fields, the heuristic feedback is now working properly
for multi-line table data capturing and generates the correct
output. Previously, the multi-line table data was not extracted even after providing the heuristic feedback. As a result, the output was not generated properly. Service Cloud Case ID: 01944805, 01946809, 01952836, 01957090, 01975800, 01981088, 01944805, 01946809, 01952836, 01957090 |
For Microsoft Standard Forms, the table extraction no longer fails when cells are empty and users can extract the document successfully. |
When a user imports a leaning instance and process the documents, the extracted document shows the correct order of words for dates in all the pages. |
When a user imports a learning instance and
process the documents, all the values are displayed in the table after
extraction. Previously, in such cases, the system-identified region (SIR) was highlighted but an empty value was shown in the table. |
When a user imports a .dw file with
heuristic feedback and process a document that contains (-) value in the
last row, the documents are extracted correctly without skipping the
negative value in last row. Previously, in such cases, the last row was skipped resulting into either data loss or incorrect processing. |
When a user processes a document that
contains table, the extraction finishes successfully without the
DOCUMENT_PARTIALLY_FAILED or Extraction
Timeout error message. Previously, in such cases, some documents were not extracted because of multiple detections from the same table and caused table size (max () arg) issue. |
When a user imports a learning instance and process the documents, all the rows are extracted separately from all pages. Previously, rows from second page were merged into one row. |
Limitations |
---|
When a user uses the Google Vision OCR, the
table detection or extraction will not work. Workaround: It is recommended to use the ABBYY OCR engine. Service Cloud Case ID: 01995901 |
In specific cases, where the tables are spanned across multiple pages without headers in all the pages (header less pages), users might observe that the data is not getting extracted from all the pages after applying the feedback. |
3.30.24
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
Fixes |
---|
Users can now view the extracted data from second row correctly by using the heuristic feedback. |
For the Purchase Order document type, you can now extract the table field values correctly from all the pages. |
The generated feedback file no longer shows any error message and users can process documents successfully. |
3.30.22
- Compatible Bot Agent version: 21.252 or later
- Compatible Control Room version: 19223 or later
What's new |
---|
Document Automation provides an improved extraction through new Get document data and Update document data actions. You can use these actions to apply custom logic for data manipulation and validation to reduce manual verification efforts. |
3.30.21
- Compatible Bot Agent version: 21.98 or later
- Compatible Control Room version: 15345 or later
Fixes |
---|
This Document Extraction package release is a patch to fix the '501: DOCUMENT_PARTIALLY_FAILED' error that occurred while processing some documents. |
3.30.19
- Compatible Bot Agent version: 21.98 or later
- Compatible Control Room version: 15345 or later
Fixes |
---|
The Document Extraction package provides improved
extraction capability for complex table header columns.
Follow these steps to enable improved table header data
extraction:
|
3.29.17
- Compatible Bot Agent version: 21.98 or later
- Compatible Control Room version: 15345 or later
Fixes |
---|
The Document Extraction package has extraction improvement fixes for both form and table fields. |
3.29.14
- Compatible Bot Agent version: 21.98 or later
- Compatible Control Room version: 15345 or later
What's new |
---|
Document Automation provides an improved extraction through heuristic feedback with a focus on complex scenarios, such as multitables. Additionally, there are extraction improvements for both form fields and out-of-the-box performance (specifically for table fields). |