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A non-profit financial cooperative in the Northeast United States, with 7 branches, offers a range of banking services, including personal accounts, business lending, and mortgages to over 45,000 members. Operating under strict regulations, they maintain extensive documentation covering policies, procedures, and compliance requirements across departments. The credit union approached Master of Code Global with a specific request: create an assistant to help internal staff quickly find answers from their information library without exposing sensitive data to external AI services.
This was our second project with this organization. Last year, we developed AI-driven conversation simulators to enhance their customer service training. The credit union needed a scalable solution to improve service quality and reduce the time required to bring new staff up to proficiency.
We created an interactive training platform using anonymized customer interaction data to simulate realistic conversation scenarios. Staff could practice handling various situations: from routine account queries to complex financial discussions and complaint resolutions. The system featured dynamic conversation flows, allowing employees to refine their skills in a controlled environment.
Over 1,500 employees completed the program. Customer support satisfaction scores increased by 17%, and average resolution time improved by 1.6 times. Building on this success, they approached us with their next operational challenge.
Internal teams at the credit union used to spend considerable time searching through policy documents, procedure manuals, and compliance guidelines. While quick access to accurate information was essential, the existing document management method made it a time-consuming and frustrating process.
The organization had a strict requirement: the solution must operate entirely within their Microsoft ecosystem to ensure data retention is strictly within their protected infrastructure. This ruled out traditional AI chatbot solutions, which typically rely on external services like OpenAI. They required a system that could understand natural language queries, search their knowledge base, and provide valid responses, while maintaining complete data sovereignty and security.
The challenge wasn’t just about connecting to documents. It was about architecting a system that could collect information from various references, choose the optimal stack, and train models to understand the financial services context. FAQ bots might seem straightforward, but when you’re dealing with complex business processes and scattered data sources, AI engineering becomes critical.
To meet this complexity head-on, we assembled a focused team of six specialists: a solution lead, conversation designer, chatbot developer, AI trainer, QA engineer, and project manager. Over four weeks, we moved from planning to launch, working closely with internal IT, HR, and compliance units. This hands-on cooperation ensured the assistant integrated seamlessly with current operations and complied with identified standards.
The result? An intelligent workflow engine that connects to SharePoint libraries, document repositories, and knowledge bases, all accessible through natural conversations. This bot is trained in financial terminology and handles everything from simple policy lookups to intricate regulatory inquiries. We also implemented sophisticated conversation flows with robust fallback mechanisms to ensure users always receive helpful responses, even when the questions are ambiguous.
Importantly, the entire system operates within Teams, their existing collaboration platform, making it convenient for staff without requiring new tools or authentication systems. The Microsoft stack integration meant seamless deployment within the familiar environment while maintaining the security and functionality they needed.
Detailed roadmap structuring and use case validation for the AI knowledge assistant
User experience architecture, including assistant persona, dialog flows, and fallback interaction patterns
Platform installation and environment preparation within the credit union's Microsoft ecosystem
Greeting dialogs, FAQ handling, fallback responses, and comprehensive dialogue logic
Document repository setup and search functionality for secure internal data access
Custom instruction crafting, use case-specific optimization, and response refinement through several iterations
Seamless integration into the existing workspace with channel-based customizations
End-to-end testing across staging and production environments with dedicated time for issue resolution
