HR Onboarding LAM
Deploy Large Action Models (LAMs) to autonomously read HR onboarding tickets, provision software licenses, and configure payroll systems via secure API execution, eliminating manual IT bottlenecks.
The Baseline
IT and HR waste days manually provisioning software accounts, active directory credentials, and payroll for new hires. Human errors lead to delayed access, fragmented onboarding experiences, and massive administrative overhead.
Authorized LAMs read the unstructured incoming HR ticket, extract the employee's role and department, and execute direct API calls to autonomously create email addresses, assign software licenses, and set up payroll records.
Reduces employee onboarding time from days to minutes with zero IT bottlenecks. New hires receive Day 1 access flawlessly, while HR and IT teams reclaim thousands of hours annually.
Architecture Flow
Ticket Ingestion
An HR manager submits a new hire request in a ticketing system (e.g., Jira or ServiceNow) containing unstructured details (name, start date, role, department). The LAM securely reads the payload.
Contextual Retrieval (Y-Ray Data)
The agent queries the internal IT provisioning matrix via Y-Ray Data to determine the exact software bundle, hardware requirements, and network permissions authorized for that specific role.
Sequential Execution (MCP)
Using the Model Context Protocol (MCP), the LAM securely authenticates with the enterprise's identity provider (e.g., Okta or Active Directory) to generate the employee's core credentials.
Platform Provisioning & Confirmation
The LAM continues its multi-step execution, using MCP to trigger APIs across disparate platforms: creating a Slack account, assigning an Office 365 license, and initializing a payroll profile in Workday. The Orchestration Engine verifies all actions and emails a finalized Day 1 setup guide directly to the new hire.
Core Infrastructure
| Component | Role |
|---|---|
| Large Action Models (LAMs) | Transforms unstructured HR text into a structured sequence of executable IT commands across multiple disconnected enterprise platforms. |
| Model Context Protocol (MCP) | Acts as the secure, deterministic bridge, allowing the AI agent to execute state-changing actions (creating user accounts) without requiring hardcoded integrations. |
| y-ray Deep-Trace | Generates an immutable, step-by-step audit log of every API call made by the LAM, proving to compliance officers exactly when, how, and why an account was provisioned. |
Technical Specifications
AES-256 for data at rest; TLS 1.3 for data in transit
SOC2 Type II, GDPR, and strict internal IT governance frameworks
Deploys natively inside your existing AWS/Azure VPC or entirely on-premise on corporate servers
Build this architecture
Map this workflow to your internal data models. Deploy AVELIN AI to gain sovereign control over your enterprise intelligence.
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