Multi-lingual skill mapping using our default taxonomy is now fully supported across all 50+ languages when using our NextGen Resume Parser.

We’re excited to share that our invoice processing models now feature instant learning from a single document. This upgrade uses the latest advancements in AI technology to deliver greater automation benefits to customers.

We're excited to announce that Affinda has launched an upgraded version of our document splitting model, delivering enhanced performance for Accounts Payable document types.

We've updated the auto-validation feature in our app, enhancing how our ability to delivery straight-through processing of your documents to reduce the level of user intervention.

The Affinda solution applies a range of post-processing steps to the raw text extracted from a document to ensure it is usable for downstream processing. Examples of this include:

To meet more customer's requirements, we have released a new option that enables customers to parse documents materially faster. The option is aimed at customers who need real-time responses where seconds count. This option is particularly relevant for Resume Parsing customers using our NextGen Resume Parser.

Customers can now sort by Collection within the Workspace view in the Affinda web app. This gives customers who are using our document classification capabilities the ability to quickly access all documents that have been left 'Unclassified' as a suitable Collection for that document has not been identified.

To align with the other documents offered by Affinda, the Job Description Parser is now visible in the Affinda Document UI through our web app. This means customers can now assess the data that has been extracted from a job description quickly and easily, without having to wade through JSON or XML formats.

Introducing our NextGen Resume Parser - the most accurate parser on the planet.

We have released our new Machine Validation Engine to give customers an even greater ability to achieve automation for their documents. Within the Affinda platform, rules can be configured to validate automatically if the data extracted by our AI models meets certain business logic, and therefore does not need any user intervention or review. Ultimately, this means that straight-through processing of documents can be acheived to remove the 'human in the loop' from the process. The rules can also be used to flag exceptions where the data does not meet expected values, ensuring accurate data for downstream processing.