Summary

A leading Workday consulting firm partnered with Marlabs to improve how consultants capture and document client requirements during onboarding. Traditional note-taking and follow-ups led to inconsistent documentation, slower onboarding, and reduced consultant engagement. To address this, Marlabs developed an AI-powered assistant that transcribes Q&A discussions, structures requirement documentation automatically, and enables seamless prototype generation. The result was faster onboarding, consistent outputs, and more time for consultants to focus on relationships instead of administrative work.

Challenge

The client needed a faster, more reliable method for capturing and documenting requirements during Workday onboarding. Manual note-taking and inconsistent summaries created inefficiencies, increased project timelines, and introduced risk in data accuracy. Consultants were spending valuable time on documentation rather than strategic engagement. The client sought to automate the capture and generation of structured requirement documentation from consultant-client discovery sessions to improve consistency, accuracy, and scalability.

Solution

AI Discovery & Use Case Definition

Marlabs began by identifying automation opportunities within the Workday discovery and Q&A process. The team collaborated with stakeholders to understand where time was lost and how data quality varied. By mapping discovery sessions, interviewing key consultants, and prioritizing use cases, Marlabs defined a clear roadmap for introducing AI automation that could integrate naturally into existing workflows.

Prototype Design & Q&A Capture

Once the use cases were defined, Marlabs designed a prototype AI assistant capable of capturing real-time Q&A dialogue. The solution incorporated speech-to-text functionality to ensure no detail was lost, as well as logic to parse and tag conversation data for structured documentation. Through iterative design and testing, the team ensured the assistant aligned with the consultant workflow, offering seamless data capture without disrupting client interaction.

Requirements Documentation Automation

After successful data capture, Marlabs focused on automating document generation. The AI assistant translated captured inputs into standardized, validated requirement documents ready for client review. Automated templates and formatting ensured every document followed consistent standards, while validation logic prevented data loss or duplication. The team emphasized quality assurance to ensure that the output was accurate, professional, and ready for deployment.

SmartLoader Integration Feasibility

To extend automation beyond documentation, Marlabs explored integration with SmartLoader and Excel (XML) environments. The team mapped prototype outputs to downstream configuration tools, enabling a more connected and automated workflow. This forward-looking phase laid the foundation for future capabilities like automated prototype generation and AI-driven configuration management, ensuring long-term scalability and efficiency for the client.

Results

The AI assistant transformed the client’s onboarding process, eliminating manual note-taking and improving documentation consistency. Consultants could now focus on client engagement without sacrificing accuracy. Automated transcription and structured documentation shortened onboarding cycles, improved delivery quality, and established a scalable framework for future AI-driven enhancements.

Impact

• Accelerated onboarding processes by reducing time from discovery to prototype.
• Eliminated information loss with real-time transcription and structured data capture.
• Increased consultant efficiency by reducing administrative overhead.
• Standardized documentation outputs across all projects and teams.
• Enhanced readiness for future AI & automation initiatives with an established framework.
• Improved client confidence through high-quality, validated documentation deliverables.