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EMRO.AI

Case Study: Transforming Contract Tracking for Contact Centers with QutrOS


Client Background For confidentiality, we will call this client Outsource Solutions Inc., a mid-sized BPO specializing in contact center services for global telecom and financial services brands. Outsource Solutions Inc. manages multiple large-scale client contracts with complex Service Level Agreements (SLAs), Statements of Work (SOWs), and Change Notices (CNs). Historically, they faced significant challenges in tracking obligations, deadlines, and performance metrics across different teams.


Problem Statement Outsource Solutions Inc. was struggling with manual tracking of contractual obligations. The finance and operations teams frequently missed key deliverable dates, leading to penalties and strained client relationships. Additionally, leaders lacked real-time visibility into compliance status, making it difficult to proactively manage risks. Despite having a capable IT team, they lacked the AI expertise to automate and streamline these processes.


Emro.AI’s QutrOS Solution After a thorough assessment, Emro.AI proposed a hybrid approach (Option C) where Emro.AI would build the initial GPT model and maintain it in partnership with Outsource Solutions Inc.’s leadership, IT, and CISO teams. This approach ensured that the client received a robust, scalable solution while building their internal AI literacy over time.


Implementation Steps

  1. Contract Data Ingestion: Emro.AI’s team collaborated with the client’s IT department to ingest all historical contracts, including SLAs, SOWs, and CNs, into QutrOS. The model was fine-tuned to recognize key contractual obligations and extract milestones.


  2. GPT Fine-Tuning: Using historical data, the model was fine-tuned to predict upcoming obligations and flag potential risks. A series of prompt templates were designed to enable finance and operations teams to query the model in plain language.


    Example prompts:

    • “List all upcoming SLA deliverables for the next 30 days.”

    • “Identify obligations due within the next week that have not yet been assigned.”


  3. AI-Literacy Training: Over three weeks, Emro.AI provided on-site and virtual training for cross-functional leaders in finance and operations. This included:


    • Understanding how to query the GPT model effectively.

    • Recognizing patterns in outputs to improve prompt engineering.

    • Ongoing mentorship to fine-tune prompts and interpret results.


  4. Compliance Dashboard: A real-time compliance dashboard was developed to provide visibility into obligation tracking, with automated alerts for upcoming deadlines and potential non-compliance risks.


Results Within three months of implementation, Outsource Solutions Inc. experienced significant improvements:


  • 98% Reduction in Missed Deadlines: With real-time visibility and automated alerts, teams were able to meet deadlines consistently.


  • 30% Increase in Operational Efficiency: Automated tracking reduced the time spent by finance and operations teams on manual reviews.


  • Improved Client Relationships: By proactively managing obligations, Outsource Solutions Inc. regained client trust, leading to contract renewals and upsell opportunities.


Next Steps Emro.AI continues to support Outsource Solutions Inc. by:


  • Expanding the GPT model’s scope to include financial forecasting and risk assessment.


  • Introducing advanced analytics to predict client escalations based on obligation trends


  • Providing quarterly AI-literacy refreshers for new and existing team members.


Conclusion This case study highlights the power of a hybrid approach in deploying customized GPT models for BPOs. By combining Emro.AI’s expertise with internal team engagement, Outsource Solutions Inc. achieved a scalable solution that drives both immediate and long-term value. Whether your organization needs a fully managed AI solution or a collaborative build-and-train model, Emro.AI’s QutrOS platform offers a proven path to success.

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