SophieX4Agent - Scaling AI Adoption in Global Service Operations through Agent Augmentation

Client: Stefanini

Team: Innovation - Global

Role: Product Manager

Product: SophieX4Agent Platform

Overview

SophieX4Agents is an AI-driven service operations platform designed to streamline and scale customer support across voice and chat channels.

By leveraging Large Language Models (LLMs), Microsoft Azure Speech Services, and integrations with ITSM platforms (ServiceNow, 4me, etc), the platform enables intelligent automation, real-time assistance and multilingual support.

It integrates with telephony systems (such as Genesys) via SIP, allowing centralized and scalable global operations.

Modern service operations face three core challenges:

• High operational costs

• Fragmented knowledge and inconsistent resolution quality

• Difficulty scaling multilingual support

SophieX4Agents addresses these challenges by:

• Automating repetitive interactions

• Assisting agents in real time with AI-powered tools

• Enabling centralized, multilingual support operations

• Improving resolution speed and consistency

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Success Metrics

We measure success through:

• Reduction in Average Handle Time (AHT)

• Increase in First Contact Resolution (FCR)

• Customer Satisfaction (CSAT)

• Operational cost reduction

• Faster ticket resolution within ITSM platforms

My Role - Product Manager (AI & Service Operations)

I joined the product as a Product Manager with the mission of connecting business, operations, delivery and engineering teams, improving product adoption and driving AI-powered innovation.

My role combined product strategy, discovery, delivery and operational alignment.

Discovery & Product Insights

Understanding low adoption of AI features

One of the key challenges was the low adoption of AI-powered features, particularly those related to Knowledge Base (KB) automation.

I led a discovery initiative with service agents across regions to understand the root cause.

Key insight

The problem was not the product itself.

It was:

• Insufficient and outdated Knowledge Bases

• Lack of training for agents

• Low familiarity with the platform

Actions driven by discovery

• Implemented cross-region training programs for agents

• Introduced guided testing environments, allowing agents to explore features outside live tickets

• Recommended feedback loops between agents and Knowledge teams to improve KB coverage

Impact

• Increased adoption of AI features

• Improved agent confidence using the platform

• Strengthened alignment between product, operations and knowledge management

Product Improvements

Configuration Manager Redesign

The configuration experience for agent numbers and resources was complex and error-prone. I led a usability study with operations teams to identify friction points.

What we did

• Reworked the structure and flows of the configuration manager

• Simplified usability and reduced cognitive load

• Improved clarity for operational teams

Impact

• Higher adoption and usability

• Reduced dependency on support teams

• Fewer operational errors

Product Delivery & Execution

Acting as Product Owner

In addition to strategic responsibilities, I acted as Product Owner to:

• Manage backlog prioritization

• Align stakeholders across regions

• Improve delivery efficiency

• Focus teams on high-impact initiatives

Process Automation (Jira)

I idealized and automated internal workflows between support, implementation and product teams.

Impact

• Reduced communication noise

• Improved ticket flow and prioritization

• Increased operational efficiency across teams

Innovation - Real-Time Translation

Led the development of a pilot for real-time translation, where Sophie acted as a live interpreter during service interactions.

What this enabled

• Real-time communication between agents and customers in different languages

• Reduced dependency on multilingual teams

• Opened the path for global service scalability

  
  

Strategic value

This initiative reinforced SophieX4Agents as an agent augmentation platform, not just an automation tool.

Key Takeaways

• AI adoption is not only a product challenge — it is also an operational and behavioral challenge

• Strong discovery can uncover problems beyond the interface

• Aligning product, operations and knowledge management is critical for success

• AI delivers more value when augmenting humans, not just replacing them

• Small process improvements (like workflow automation) can generate significant impact

Final Reflection

This experience strengthened my ability to:

• Operate in complex, enterprise environments

• Lead cross-functional alignment across global teams

• Drive AI product strategy with real operational impact

• Bridge the gap between product, operations and user behavior