How to Use Make.com and Vision AI for Automated Document Verification in HR Onboarding

In today’s fast-paced HR environment, manual document verification during onboarding is not only time-consuming but also prone to human error. This guide provides a detailed, step-by-step approach to leveraging the powerful automation capabilities of Make.com (formerly Integromat) in conjunction with Google Cloud Vision AI to automate and streamline the document verification process, enhancing efficiency and accuracy for HR teams.

Step 1: Set Up Your Make.com Scenario and Initial Trigger

Begin by creating a new scenario in Make.com. The first module in your scenario will be the trigger that initiates the document verification process. For HR onboarding, common triggers include a new file upload to a shared drive (like Google Drive or SharePoint), an email attachment received, or a new entry in an HRIS (Human Resources Information System) that flags a document for verification. Select the appropriate module—for instance, “Google Drive > Watch new files” or “Email > Watch emails”—and configure it to monitor the specific folder or email inbox where new onboarding documents are deposited. Ensure the connection to your chosen service is established correctly, allowing Make.com to access the incoming documents.

Step 2: Integrate Google Cloud Vision AI for Document Processing

Once your trigger is set, the next crucial step is to integrate Google Cloud Vision AI. Add a “Google Cloud Vision” module to your Make.com scenario. The specific action you’ll use depends on the type of verification. For extracting text from documents (like passports, IDs, or diplomas), choose “Perform OCR (Optical Character Recognition)” or “Detect Text.” For more complex visual analysis, such as detecting logos or specific features, other options might be suitable. You will need to provide your Google Cloud Platform credentials (typically a service account key) to authenticate the connection. This step bridges the gap between your incoming documents and the powerful AI capabilities of Google’s vision services, readying them for analysis.

Step 3: Configure Vision AI for Specific Data Extraction and Analysis

Within the Google Cloud Vision AI module, meticulously configure its settings to target the specific information you need to extract and verify from your HR documents. For instance, if verifying an ID, you’ll want to extract the name, date of birth, document number, and expiration date. Vision AI’s OCR capabilities are highly robust; ensure you select the correct language settings for the documents you’re processing. Beyond simple text extraction, consider using features like “Web Detection” or “Face Detection” if applicable to your verification needs, though text-focused analysis is typically paramount for onboarding. The precision of this configuration directly impacts the accuracy and reliability of your automated verification, making it a critical phase.

Step 4: Implement Verification Logic and Data Comparison

After Vision AI processes the document and outputs the extracted text, the next step in Make.com is to implement the core verification logic. This involves comparing the extracted data with existing employee records in your HRIS or a database. Use Make.com’s “Router” and “Filter” tools to create branching pathways based on verification outcomes. For example, you might use a “Text Parser” module to isolate specific fields from Vision AI’s output, then a “Search Records” module (e.g., in Google Sheets, Airtable, or your HRIS via API) to find a matching employee record. Filters are then applied to check if the extracted name matches the database, if the document is valid based on an expiration date, or if required fields are present and accurate.

Step 5: Automate Conditional Routing and HR System Updates

Based on the outcomes of your verification logic, set up conditional routing within Make.com to automate subsequent actions. If a document passes all verification checks, you might use a module to update the employee’s record in your HRIS, mark the document as “verified,” or move it to a “verified documents” folder. If verification fails, the scenario can automatically trigger an email notification to the HR team, flag the document for manual review, or even send an automated message to the new hire requesting clarification or a corrected document. This intelligent routing ensures that only fully compliant documents proceed, while anomalies are immediately escalated for human intervention, significantly reducing manual oversight.

Step 6: Implement Error Handling and Notification Systems

Robust automation requires comprehensive error handling. Within your Make.com scenario, integrate modules that can catch and manage potential issues that arise during the document verification process. This includes configuring modules to notify relevant personnel via email or internal communication tools (like Slack or Microsoft Teams) if a scenario execution fails, if Vision AI returns an unexpected error, or if a document cannot be processed. Furthermore, consider adding “Sleep” modules or “Retry” directives for certain operations that might occasionally encounter temporary network issues or API limits. Proactive error management ensures that no document verification falls through the cracks and that HR teams are promptly informed of any discrepancies requiring their attention, maintaining workflow integrity.

Step 7: Test, Refine, and Deploy Your Automated Workflow

Before fully deploying your automated HR document verification workflow, thorough testing is paramount. Run the Make.com scenario with a variety of test documents, including both correctly formatted and intentionally erroneous ones, to ensure all branches of your logic function as expected. Pay close attention to how Vision AI extracts data from different document layouts and how your filters handle discrepancies. Based on testing, refine your verification logic, Vision AI configurations, and notification systems. Once confident in its reliability and accuracy, activate the scenario for live operation. Continual monitoring and periodic reviews will help optimize performance and adapt to evolving HR or document requirements, making your onboarding process incredibly efficient.

If you would like to read more, we recommend this article: Make.com: Your Maestro for AI Workflows in HR & Recruiting