We are excited to announce that customers now have the ability to add custom fields to our 'off the shelf' models. This feature empowers customers to capture and utilize any data that is specific to their unique use cases.

In addition, we have implemented a predictive data functionality that can automate the process of filling in these custom fields.

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Not available for Recruitment AI customers at this time

Custom field predictions are only suitable for Accounts Payable and Compliance document types currently

Adding Custom Fields:

To add custom fields to your tailored invoices, edit your field configuration in your Collection Settings page or by clicking Edit within the Validation UI in the app. Click '+' to add a new field and then specify:

• Label - this is what is shown in the Validation UI
• Data Point Type - this influences any post-processing applied (e.g. data, number formatting)
• Data Point Slug - auto-generated from the label, but can be edited
• Multiple? - specify if there could be multiple examples of the data point in the document, or only once

Training the custom field

Enabling Predictive Data with OpenAI

If consent to use OpenAI is enabled for your account, you can leverage its capabilities to predict the values of custom fields based on existing examples. Here's how it works:

1. Initial Validation: Validate one document with the desired custom field and manually label the data point.
2. OpenAI Prediction: Once the initial validation is complete, OpenAI will analyze the labeled example and predict the custom field's value for new documents.
3. Accumulating Examples: Continue validating additional documents with the custom field until you have a minimum of 10 examples.
4. Model Predictions: Once you have enough examples, our own models will take over the prediction task, replacing OpenAI.

Using Manual Labeling (Without OpenAI)

If consent to use OpenAI is not enabled for your account, you can still benefit from custom fields by manually labeling the data points. Follow these steps:

1. Manual Labeling: Validate each document individually and manually label the values for the custom fields.
2. Accumulating Examples: Label the data points for each document until you have enough labeled examples for accurate predictions.

We understand that you might want to add new data fields to your Collection after you have already added and validated some documents for training. With our system, you can easily add new data fields at any point in the process. The model will only train that data point on documents added after the data point was created, meaning users won't need to go back through their backlog of documents to correct the data for the new field.

Affinda has integrated with OpenAI's GPT family of large language models to enable a seamless and immediate experience when creating new models and when adding new fields to existing models.

With our OpenAI connection, Affinda now offers "one-shot learning," meaning that you only need to provide one annotated example document to start making accurate predictions on subsequent documents.

This means you can begin utilizing the models almost instantly, and their performance will only improve over time. As we transition from OpenAI-generated predictions to Affinda's standard model framework, which delivers faster and more precise results when ample data is available, the quality of results will continue to excel.

When OpenAI is used

Affinda may leverage OpenAI's technology in the following scenarios:

1. Creating a new custom extractor.
2. Adding a new custom field to one of Affinda's standard extractors, such as invoices.

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No data is shared with OpenAI when using our 'off-the-shelf' models

We do not share any data with OpenAI for model training if you are using our standard models (e.g. resume, job description, passports, etc.), even if you have given consent

Respecting your consent

As Affinda utilizes OpenAI's technology, we value your consent to utilize this integration. Customers have the option to opt-out when creating new Collections or through the Collection Settings page at any time if they prefer Affinda not to send documents to OpenAI.

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Opting out of using OpenAI does not restrict the creation of custom extractors or fields

However, it does require customers to manually label all data in the initial set of documents (approximately 50) before an Affinda model can be created without any predictions provided. This may increase the manual effort required

For more information on creating custom models or adding custom fields to a standard extractor, please get in touch.

Our latest API version, API v3, now supports the seamless adding and updating of resume and job description data, including custom fields. This improvement resolves compatibility issues experienced with API v2 and ensures a smoother experience for all users.

Key Features

1. Resume Data Updates: Modify resume data programmatically with API v3. When recruiters or candidates edit the information in your platform, this gets reflected in Affinda's system and flows through to our Search & Match product.

2. Job Description Updates: Update job description details, including qualifications and responsibilities, to enhance the Search experience.

3. Create from data - create resumes or job descriptions directly from your existing data, meaning you don't need to reparse documents

4. Custom Field Support: Add and update custom fields that suit your specific requirements.

5. Improved Compatibility: API v3 resolves previous compatibility issues, ensuring that users can stay using the latest API version at all times.

Get Started

Resumes or job descriptions can be created from 'data' using the Upload a document for parsing endpoint.

Updating of resume and job description data is available via the Update a document endpoint. (For other document types, please use Update an annotation or Batch update annotations.

Our latest update allows you to request a custom model tailored to your needs, right from within our app! Unlock a more personalized document processing experience that achieves greater accuracy and delivers even greater efficiency gains.

This feature is perfect for invoice extraction, but can also be applied to other document types where it makes sense. To request a tailored model, simply go to the Collection settings or field layout configuration interfaces.

Once you submit your request, our customer support team will configure a model that suits your requirements, ensuring accurate and efficient data extraction.

We have released a new and enhanced Field Configuration Interface within our app to deliver greater control and customization options for managing fields in our platform.

Key features of the new Field Configuration Interface include:

• Reorder and Group Fields: Easily customize the arrangement of fields to suit your needs.
• Edit Field Configuration within the Validation Interface: Streamline your workflow by editing field configurations directly within the validation interface.
• Enhanced Collection Settings Page: Seamlessly manage and configure fields through the integrated Collection settings page.
• Create Custom Fields: Tailor your fields by specifying the type, label, and whether multiple annotations are allowed within a document.

To explore the new Field Configuration Interface, simply log in to your account and navigate to the respective sections.

In our continuous efforts to safeguard your data and ensure the highest level of security, we are making a change to the way API keys are managed within the application.

What has changed?

We have now encrypted the API key within the Affinda app to provide an additional layer of security. As a result, after creating an API key, users will no longer be able to retrieve it from the application. Instead, we have introduced a new feature that allows users to generate up to three API keys. This will facilitate key rotation without disrupting your production environment if you choose to do so.

How does the new key rotation feature work?

With the key rotation feature, you can manage your API keys more effectively. Here are some key points to be aware of:

• Viewing the key: Once you create a key, you will only be able to view it once within your user settings page in the application. It is crucial that you copy and store it in a safe location within your own environment.
• Maximum of 3 API keys: You can generate a maximum of three API keys within the Affinda app.
• Naming and Expiry: Each API key can be named and set with an expiry date or to never expire, based on your requirements.

Action Required (if applicable)

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If you have already stored your existing API key, there is no immediate action required on your part. Your current API key will continue to function normally.

If you have not stored your API key yet, you will need to generate a new API key within the Affinda app to access it. Remember, you will only be able to view the key once, so ensure you copy it accurately (or you can generate a new key next time you need it).

We're thrilled to announce that Resumes are now viewable in the Affinda Validation Interface. With this new feature, users can now access and analyze the data extracted from resumes directly within our validation interface. The validation interface now displays relevant data extracted from resumes, allowing users to review and analyze parsed information conveniently. Gone are the days of manually cross-referencing data points!

The extracted data shown in the interface includes crucial elements such as personal information, contact details, work experience, education, and skills.

However, it is important to note that it does not include all data that would be returned through the API such as certifications, publications, and referees. In addition, any additional data mapped to the data extracted from resumes, such as management level, occupation classification, and skill taxonomies, are not included in the visualization. We recommend analyzing the full range of data parsed from the Affinda solution by referring to the schema here or by viewing an export of some sample resumes.

For existing customers, this change will have no impact on your solution. You can log in to the Affinda app to view the visualizations, however, this will not impact your use of the API to return candidate data.

We're excited to announce a new feature for our validation tool that makes it even easier to seamlessly integrate our technology into your own platform. With our latest update, users can now customize the theme of our validation tool to match their own branding all from within the Affinda app, making it a perfect white-labeled solution for any organization.

The theme customization options are available exclusively when the validation tool is used in embedded mode, so users can create a truly integrated experience for their own customers. From the Organization settings page, users can adjust the colors and border radius for both light and dark modes of the validation tool, ensuring it fits seamlessly into any design scheme.

In addition to the theme customization options, we also offer further customization options for fonts and actions shown. If you're interested in exploring these options, please don't hesitate to get in touch with our team. We're always happy to work with our customers to ensure our technology meets their unique needs.

We are excited to announce the release of a new feature in our candidate search user interface that will greatly improve the search experience for our users. Customers can now search across additional 'custom' data fields that are not included in our standard categories using the Affinda Search Interface.

With this new feature, end-users will be able to seamlessly search across these custom fields as they do with the other search fields, providing greater flexibility and accuracy in their search results.

Custom fields can be of the following types:

• Text
• Boolean
• Number
• Date

For more information, see Customising and Embedding the Search UI.

With this new addition, customers no longer need to spend time and resources setting up the API integration to send their documents to us. It is a convenient and hassle-free solution for those who prefer to use email for document sharing and means that the data extraction process can fit seamlessly within your existing processes.

The process is simple, all customers need to do is attach their documents to an email and send it to a specific email address provided by us. Our system will automatically extract the attachments and apply our AI models to process them accordingly.

Email addresses to use for uploading documents can be found in the Settings panel of all Workspaces and Collections. (Each Workspace and Collection will have a unique email address associated with it.)