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Onboarding Handbook Generator Agent automates the creation of personalized onboarding handbooks for new hires. By leveraging a Large Language Model (LLM), it integrates job role requirements, departmental guidelines, and company policies to generate tailored handbooks that enhance onboarding consistency, reduce manual effort, and support early employee engagement.

Challenges the ZBrain Onboarding Handbook Generator Agent Addresses:

Creating personalized onboarding handbooks is often a manual and time-intensive process for HR teams. It requires compiling role-specific details, departmental policies, training resources, and compliance information—all of which are prone to inconsistency and human error. As organizations scale and diversify their roles, delivering accurate and role-specific onboarding materials becomes increasingly difficult. Inconsistencies in onboarding affect employee experience and can lead to misunderstandings and lower initial productivity.

ZBrain Onboarding Handbook Generator Agent streamlines the process by automatically generating customized onboarding guides based on each new hire’s role, department, and profile. It pulls structured content from internal knowledge bases and combines it with job-specific insights using LLM. Each handbook includes relevant training materials, compliance checklists, cultural insights, key contacts and other relevant sections—ensuring every new employee receives a complete and accurate guide. This automation ensures a consistent onboarding experience, minimizes manual workload, and improves early-stage engagement and alignment.

How the Agent Works?

The onboarding handbook generator agent is designed to automate the generation of customized onboarding handbooks for new hires. The agent accesses multiple knowledge bases to retrieve essential details for various sections of onboarding handbooks and leverages a Large Language Model (LLM) to craft a customized, comprehensive handbook specific to the new hire's name, profile and job role. Below, we outline the detailed steps of the agent's workflow, from inputting the candidate's profile to the continuous improvement of the agent.

Step 1: Input Collection

Upon the new hire's registration in associated systems or receiving details through the agent's interface, the agent activates to gather essential inputs needed to generate a tailored onboarding handbook.

Key Tasks:

• Name and Role Details Capture: The agent captures the new hire's name and job role to precisely tailor the onboarding handbook, ensuring the collection of relevant details for delivering personalized and role-specific resources.
• Knowledge Base Selection: The agent is configured with multiple knowledge bases, each associated with a unique ID and stored in an array. During the deployment of the agent, the user specifies which knowledge bases to include, ensuring all relevant knowledge bases for the company's various roles are covered. Once deployed, the agent automatically selects appropriate knowledge bases depending on the new hire's specific role to create the handbook. This ensures that each handbook is tailored accurately to the role's requirements using the correct knowledge base.

Outcome:

• Data Foundation Established: This step secures the foundational inputs required to generate a personalized onboarding handbook, setting initial parameters that guide customization to match the new hire's role and requirements effectively.

Step 2: Knowledge Base Access for Required Information

Upon acquiring the new hire's specific details, the agent accesses multiple configured knowledge bases. Being a comprehensive document, the onboarding handbook necessitates retrieving detailed information from various organizational sources.

Key Tasks:

• Search Relevant Information: Utilizing the new hire's details and the identified knowledge bases, the agent systematically searches for relevant information, such as file names and IDs associated with specific handbook sections like the Welcome Section or Company Policies.
• Fetch Information: After identifying the relevant file IDs, the agent extracts as much pertinent information as possible from these files to assemble sections of the onboarding guide.
• Pass Information to LLM: The extracted details are then passed to the Large Language Model (LLM) for further refinement and integration into the handbook.
• Repeat for Other Sections: This process is repeated for each section of the handbook, ensuring comprehensive coverage and customization of the entire document. These sections can include company overview, department information, role-specific information, systems access, policies and procedures, training and development and more.

Outcome:

• Comprehensive Data Compilation: This step ensures all relevant data is gathered, structured, and prepared for final processing, setting the foundation for a detailed and personalized onboarding handbook.

Step 3: Customized Onboarding Handbook Generation

Once the essential information is collected, it's processed by the LLM to create a customized onboarding handbook tailored to the new hire.

Key Tasks:

• LLM Processing: The LLM processes and refines the fetched information to compile the structured sections of the handbook.
• Tailored Handbook Generation: The LLM compiles refined and customized sections to generate a comprehensive copy of a user-specific onboarding handbook.

Outcome:

• Customized Handbook Draft: Produces a fully tailored onboarding handbook, ensuring it is relevant and personalized to effectively support the new hire's integration.

Step 4: Continuous Improvement Through Human Feedback

After the onboarding handbook is generated for new hires, the agent can integrate feedback from users to refine the handbook content for future candidates and adapt to evolving company policies.

Key Tasks:

• Feedback Collection: Users can provide feedback on the handbook's relevance, comprehensiveness, accuracy and usability. This feedback is crucial for identifying content gaps or outdated information.
• Feedback Analysis: The agent evaluates feedback to identify areas for improvement.
• Continuous Learning: Based on the feedback received, the agent adjusts its content generation and structuring processes to improve the accuracy and effectiveness of future handbooks.

Outcome:

• Continuous Enhancement: With each feedback cycle, the agent can improve the handbooks, increasing their accuracy and relevance. This continuous learning process enables the agent to more effectively meet the needs of new hires and helps align the onboarding experience with the company’s evolving goals and workforce development strategies.

Why use Onboarding Handbook Generator Agent?

• Efficiency: By automating onboarding handbooks, HR teams can save time and focus on other high-impact activities.
• Consistency and Accuracy: The agent uses standardized information to ensure each handbook is accurate and consistent, providing new hires with quality information tailored to their roles.
• Customization: Handbooks are customized based on role-specific details and company policies, ensuring relevance to each new hire's position and department.
• Enhanced Employee Experience: Personalized handbooks make new hires feel valued and informed, significantly improving their initial experience and engagement with the company.

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By automating the assembly of training materials, the Training Material Compiler Agent reduces manual work for HR teams and ensures consistency in the onboarding process. This agent not only accelerates the training phase for new hires but also improves their readiness by providing them with a customized set of resources. The agent continuously updates training content as new materials are added, ensuring that employees always have access to the latest information and training tools required for their roles.

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Human Resources

Onboarding Handbook Generator Agent

Generates customized employee handbooks tailored to company policies, job roles, and department-specific guidelines.

Human Resources

Training Material Compiler Agent

Compiles training materials specific to the new hire's role, gathering content from existing resources like manuals, guides, and e-learning modules.