Transforming Enterprise AI for a Leading HCM Provider

Our client, a leading provider of human capital management solutions, is embracing the future of work by integrating AI into its ecosystem. With an ambitious roadmap aimed at improving productivity, enhancing customer experiences, and driving innovation, our client turned to Launch Consulting to provide the AI expertise and engineering power necessary to make this vision a reality.  

By embedding skilled cross-functional teams into our client's operations, Launch is enabling faster development, greater flexibility, and stronger alignment with evolving business priorities. Our multi-disciplinary team of AI and Cloud architects and data and software engineers are building advanced AI agents to optimize business processes and enhance customer experiences across our client’s platforms.  

The Challenge

Our client sought to unlock the full potential of AI across its internal operations and external customer-facing applications. This required:

• A scalable approach to AI development that could support multiple teams and initiatives.

• Modernization of its cloud environment to better support agent-based architectures.

• Fast-tracking generative AI integration while managing risk and compliance.

• Clear alignment between AI engineering, data strategy, and business goals.

The Solution

To support our client’s AI roadmap, Launch activated two targeted workstreams—each focused on delivering intelligent agent capabilities through enterprise-grade architecture and agile execution.

Workstream 1: Dialogflow Virtual Assistance Enhancement

This stream centers on enhancing the client’s customer experience by evolving the virtual assistant embedded in the Flex application.

Key Outcomes:

• Dialogflow-Powered Customer Agent
  Launch brought deep Dialogflow CX expertise to evolve the client’s chatbot into a production-grade, AI-enhanced customer support solution.

• Generative AI Integration
  Existing flows were augmented with new generative AI capabilities, delivering more natural and helpful conversations.

• Performance Optimization
  AI performance is continuously refined based on real-time customer feedback and usage analytics.

• API Integration
  The assistant now connects with key APIs, driving more personalized and actionable responses.

Workstream 2: Knowledge AI & Agentic Platform on Azure

The second stream focuses on internal AI enablement by building a robust agentic platform using LangGraph, hosted in the client’s Azure environment.

Key Outcomes:

• LangGraph Agent Development
  Launch is creating omni-channel, non-deterministic AI agents to support payroll operations, internal workflows, and data interactions.

• Centralized Knowledge Hub
  A Snowflake-powered data platform with advanced ETL pipelines was established to fuel knowledge access across agents.

• Multi-Channel Integration
  Middleware is being developed to enable agent interaction across email, voice, and chat—future-proofing the company's communication strategy.

• Enterprise-Grade Platform Architecture
  Launch is responsible for the infrastructure build-out—hardening, scaling, and enabling CI/CD through GitHub Actions and Azure DevOps.

By aligning these agents with the client’s roadmap, Launch is not only solving immediate needs but also delivering a flexible architecture that will power future AI innovation across the enterprise.