Automated Evidence Testing (AET) is currently available for the Controls Compliance and Internal Audit Management applications only. For other use cases, please contact your account team or submit a feature request.
Overview
Automated Evidence Testing is an AI Skill part of LogicGate AI capabilities that extends automation beyond evidence collection to evidence review—enabling continuous, agent-driven control monitoring. AET evaluates each evidence attachment against your defined testing procedures and returns a recommended testing outcome (pass, fail, or incomplete), along with clear testing rationale and remediation guidance.
Instead of relying on point-in-time audits, evidence is validated automatically as it is submitted. When paired with Automated Evidence Collection (AEC), evidence can be both collected and reviewed without manual intervention—shifting compliance programs from periodic, manual testing to always-on assurance, with reviewers remaining in full control through human-in-the-loop validation.
How to Enable AET
1. Log in to LogicGate platform as an admin user.
2. Go to Admin > AI Control Center to enable Automated Evidence Testing. Learn more about LogicGate AI here.
Note: By enabling Automated Evidence Testing, you will have access to a new Job operation card called "Run Evidence Test" when you set up the Job Automations within your application
3. Make sure your organization has access to the Controls Compliance or Internal Audit Management application. You can verify this in Application Build > App Settings > Application Use Case. Make sure one of the applicable use cases is selected.
Creating an Automation for Evidence Testing
Automated Evidence Testing is configured in Jobs. Follow the steps below to create a job that automates evidence tests when evidence records are created or moved. To learn more about Jobs, refer to the Help Center Article.
Note: The example below is based on the Controls Compliance Application template. You can tailor the configuration to align with your organization's workflows setup.
1. Navigate to Build → Jobs → + New Job.
2. Select a Trigger: Choose either Record Created or Record Move on the workflow where you want Evidence Test to run (e.g., Controls Compliance Application's Evidence Task Workflow)
Note: The Run Evidence Test job operation is currently available only for these 2 trigger types.
Common Scenario - With Automated Evidence Collection (AEC): If AEC is enabled, AEC creates new Evidence Task records on a scheduled cadence, with evidence file attached at each collection. Use the Record Created trigger on the Evidence Task workflow at the Evidence Review step.
Common Scenario - Without AEC: If you are not using AEC, you can still run evidence tests. Use the Record Moved trigger on the Evidence Task workflow, moving records from Evidence Collection to Evidence Review.
3. Add the Run Evidence Test operation. When the trigger type and prerequisites are met, the Run Evidence Test operation card will be available.
4. Configure Run Evidence Test - Select input fields:
Evidence Attachment (required): Choose an attachment field that contains the evidence file(s) to be evaluated. Automated Evidence Testing supports validation of multiple evidence files in a single attachment field.
Testing Procedures (required): Choose a text, text area, or text concatenation field that defines the testing procedure or criteria.
Control Description (optional): Select a text, text area, or text concatenation field that contains additional context about the control being tested.
Evidence Description (optional): Select a text, text area, or text concatenation field that provides additional context about the evidence.
5. Configure Run Evidence Test - Select output fields:
Testing Results (required): Select a single‑select field to store the AI‑generated outcome (e.g., Pass, Fail, Insufficient).
Testing Rationale (required): Select a text or text area field to store the AI-generated supporting rationales.
Remediation Action (optional): Select a text or text area field to store the AI-generated suggested remediations.
6. (Optional) Add Conditions or Additional Operations. Jobs that include the Run Evidence Test operation support stacking conditions and additional operations.
For example, you can configure a condition to run evidence test only when the Test Type field equals Automated if you don't want all evidence submitted goes through Automated Evidence Testing. You can also combine this with other operations, such as notifying the Evidence Owner when a test result fails.
7. Publish and Test the Job. Publish the job to enable it. Once published, the job will run automatically when the configured trigger and conditions are met. To test the job, create or move a record that triggers the job. You can verify execution details in the Job History tab.
Running Automated Evidence Testing
Triggered by Record Moved
Create a record and upload evidence. Create a record in your workflow (e.g., an Evidence Task record in the app template) and upload an evidence file. Ensure the required fields for the Run Evidence Test operation — Attachment and Testing Procedure — are populated.
Move the record to trigger testing. Move the record to the workflow step configured to trigger the Run Evidence Test job operation (e.g., from Evidence Collection to Evidence Review step).
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Review test outputs. After the record is moved, the output fields — Test Result, Rationale, and Remediation Action — will be populated once the job completes.
Note: Depending on current job volume, results may appear immediately or take up to 1–2 minutes. You can track execution details in the Job History tab.
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Output fields populated by AET are labeled “Tested by LogicGate AI.” If a user edits a value, the label is automatically removed.
Triggered by Record Created (compatible with AEC)
Configure AEC on the parent record (e.g., an Evidence Requirement record in the app template). Set up AEC to automatically create a new child record with the evidence file attached (e.g., an Evidence Task record created in the Evidence Review step).
Run AEC immediately or on its scheduled cadence. When AEC creates a new record in the workflow step configured with a Record Created trigger, the Run Evidence Test job operation is automatically triggered.
Review test outputs. Once the job completes, the output fields—Test Result, Rationale, and Remediation Action—will be populated on the newly created record.
Labels and Field History
Labels: Fields populated by Automated Evidence Testing are labeled “Tested by LogicGate AI.” If a user manually edits a value, the AI label is automatically removed.
Interaction with Autofill: Fields populated by Autofill can be overwritten by Automated Evidence Testing. In this case, the label updates from “Autofilled with LogicGate AI” to “Tested by LogicGate AI.” However, fields populated by Automated Evidence Testing are not overwritten by Autofill, as Autofill only generates content for blank fields.
Audit Trail: Every field populated by Automated Evidence Testing is recorded in the Field History side panel and is exportable as a CSV. Logged details include the field name, updated value, record ID, job name, executor (Automated Evidence Testing), record assignee, and timestamp. This provides full traceability for all AI-generated field updates.
Best Practices
Provide Clear Testing Procedures. The quality of AI-generated results depends heavily on the clarity of your testing procedures. Clearly specify what constitutes a pass or fail to ensure accurate and consistent outcomes.
Provide Additional Contexts. Use optional input fields to improve result quality: Control Description to describe control objectives and pair with the testing procedure. Evidence Description to explain the context of the attached evidence.
Review AI Outputs. AET can make mistakes, so human oversight remains essential. Always review AI-generated test results, supporting rationale, and remediation recommendations before finalizing decisions.
Combine with AEC. Automated Evidence Testing delivers the most value when paired with Automated Evidence Collection. Together, they enable continuous evidence collection and testing, helping shift programs away from manual uploads and periodic audits toward ongoing control monitoring.
Example Scenarios
Try running Automated Evidence Testing against one or multiple evidence files.
Single-File Examples:
- Privileged Access Reviews: Review a user access roster to verify only authorized individuals hold privileged or admin-level access
- Password Policy & MFA Configuration Check: Review a screenshot of identity provider settings to confirm password complexity requirements and MFA are enabled and configured according to policy
- Backup Completion Validation: Review a backup job log or report to confirm scheduled backups completed successfully and within defined retention requirements
Multi-File Examples:
- User Access Reviews: Cross-reference two CSV files to identify improper user access to internal systems
- New Vendor Security Assessments: Review new vendor security questionnaires and SOC 2 reports to identify potential red flags
- Security Awareness Training & Policy Acknowledgments: Validate completion of required trainings and policy acknowledgments for new employees
Troubleshooting
If you encounter errors in Job configuration, Job History, or if Automated Evidence Testing does not trigger as expected, review the checks below.
Supported Trigger Types: The Run Evidence Test job operation is available only for Record Created and Record Moved. If a different trigger type is selected, the operation will not be available.
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Supported File Types: The Run Evidence Test operation supports the following file types. If a different file type is uploaded, the job operation will throw an error:
- docx
- pptx
- xlsx
- csv
- json
- txt
- jpg
- jpeg
- png
- gif
- webp
- wav
- mp3
- mp4
- mpeg
- mpga
- m4a
- ogg
- webm
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Supported Application Types: The Run Evidence Test operation is available only when the Application Type is set to Controls Compliance or Internal Audit Management at the time the job is created.
If the Application Type is later changed to another use case, existing jobs that include Run Evidence Test will continue to execute as configured.
Required Input/Output fields Deleted: If any required input or output field used by the Run Evidence Test operation is deleted, the operation will be disabled. The Job Configuration will display an error prompting you to update the invalid operation. To resolve this, reselect the required input and output fields, save the operation, and publish the job.
Required Input Fields Missing Values: If any required input field is left blank, the Run Evidence Test operation will execute but appear as No Operation in the Job History. In this case, no output fields will be populated.
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OpenAI Integration & AET Feature Toggles: Disabling the OpenAI integration or the AET feature toggle disables all existing Run Evidence Test operations. The Job Configuration will display an error indicating the operation is invalid. To resolve this:
Re-enable the OpenAI integration and/or AET feature toggle.
Reselect any input or output field in the Run Evidence Test operation to save the configuration.
Republish the job. This clears the error messages and reactivates the job.
Evidence File Size Limits: Evidence files are limited to certain token limits that are allowed to processed by the OpenAI model. If the evidence file exceeds the token limit, the Run Evidence Operation will show no operation and throw an error code "File content is too large to test."
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Files with Embedded Images: Automated Evidence Testing supports processing of embedded images for the following file types:
- docx
- pptx