Knowledge Buddy for Customer Service
Casestudy: Revolutionizing Customer Service with GenAI Knowledge Buddy
A prominent cooperative pension company) modernized its customer service using Pega’s GenAI Knowledge Buddy, implemented and managed by BPM Company. Within 2.5 months, a dedicated GenAI service was live—integrated via APIs, continuously synchronized, and built with enterprise-grade RAG architecture. The result: faster, customer responses, reduced operational costs, and enhanced agent efficiency.

Client overview
A large cooperative pension investor in the Netherlands engaged BPM Company to enhance its customer service operations. The organization supports multi-channel interactions via telephone, chat, email, and an online self-service portal. Six months ago, they began using Pega GenAI Knowledge Buddy to elevate their service model, building upon an extensive existing knowledge management portal.
Business challenge
The client had a strong knowledge base but faced inefficiencies: information was scattered across numerous articles, which complicated and slowed responses. Their goal was to streamline agent workflows, reduce response times, and ensure reliable, up-to-date answers—regardless of channel. They sought an AI-enabled knowledge assistant that would deliver concise, accurate, and consistent customer support.
How Pega’s GenAI Knowledge Buddy Enabled the Solution
To tackle these challenges, BPM Company collaborated with Pega and the client to set up a dedicated Knowledge Buddy environment. Pega provisioned a separate server, URL, and sandbox for a proof-of-concept. BPM Company managed the POC alongside Pega—testing prompting techniques and evaluating which generative model would yield optimal performance. This led to the creation of a standalone GenAI Knowledge Buddy service.[MK1] A new data source was established for the Knowledge Buddy, synced via API’s with the client’s customer service application. When new content was added in either system, automated API calls ensured both environments stayed aligned. Within just 2.5 months, the service went live. The client quickly signed off on the final product thanks to clear guidance and involvement throughout the process.
Pega GenAI Knowledge Buddy is designed to use an enterprise knowledge base to deliver reliable answers through conversational interfaces. It leverages Retrieval-Augmented Generation (RAG) to ensure responses are accurate and traceable to source documents, and avoids hallucinations by instructing the AI to respond with “I don’t know” if content isn’t found. It seamlessly integrates via API or built-in widgets, offering strong security, auditability, and multi-channel deployment flexibility.
Why we were the ideal partner
- Local Expertise: A Dutch firm well-versed in the country’s pension and customer service landscape.
- Pega Proficiency: Deep experience in designing and implementing GenAI solutions such as Knowledge Buddy.
- System Integration Knowledge: Skilled at architecting APIs and seamless commission of new services within client ecosystems.
- Domain Insight: Familiar with the operational intricacies and regulatory demands of pension-based customer service.
Smooth implementation of Knowledge Buddy for the Customer Service
The project moved forward rapidly. From kickoff to live deployment took just 2.5 months for the newly developed GenAI service. The client’s firm guidance and clear requirements contributed to swift approval of the final solution.
Business benefits delivered
The implemented solution produced tangible value across several dimensions:
- Faster Response Times: Agents now retrieve required information in seconds.
- Efficiency and Cost Reduction: Reduced interaction time—calls are shorter and handled more effectively.
- Higher Agent Productivity: Staff can handle a greater volume of queries each day.
- Improved Service Quality: Up-to-date and consolidated information empowers agents to give better, consistent responses, even when knowledge is spread across different articles.
These align with the benefits highlighted by Pega: rapid deployment of AI assistants, improved productivity, secure integration, and better CX across channels.


