AI Knowledge Assistant for Document Search and Internal and External Support
- OpenAI
- API
- LLM
- AI Automation
- Data Processing
Product Overview
The solution was developed as part of a large-scale digital transformation initiative for a global sports governing body, aiming to provide fast and accurate access to complex internal documentation through a unified system. By combining AI-powered document search with a conversational interface, the project introduced a scalable AI knowledge system for navigating bylaws, association data, and website content.
SCAND developed an AI knowledge assistant that integrates intelligent document search with a chatbot-style interface, enabling members and administrators to query internal documentation and instantly receive relevant, context-aware answers. It also helps website visitors to answer any sports-related questions backed up by the organization’s knowledge base. The system reduces the need to manually search across multiple platforms and supports more efficient knowledge access across and out of the organization.
Designed as an AI knowledge assistant for enterprises, the solution improves knowledge management processes, reduces the workload on internal support teams, and allows users to efficiently communicate on top of the large volumes of structured and unstructured data.
- Region: Global
- Industry: Sports Governance / Membership Management / Digital Transformation
- Timeline: 3.5 months
Challenge
The client needed a more efficient way to manage and access internal knowledge without overloading support teams.The client website visitors should be able to get answers quickly on any industry related questions.
- Fragmented data across systems. Key information, including member data, bylaws, and association-related content, was distributed across a central database and a public website. This lack of synchronization created inconsistencies and made it difficult to maintain a unified knowledge management AI approach.
- Difficulty navigating complex documentation. Members and administrators struggled to find accurate answers within large volumes of documentation, regulations, and global association data. This made it clear that users needed a more intuitive way to find relevant information without spending time searching through documents. Website visitors on the other hand were limited to the FAQ provided manually.
- Inefficient knowledge access and authentication issues. Users had to switch between multiple systems and log in several times, making it harder to find information and slowing down their work.
- High workload on internal support teams. A large share of incoming questions were repetitive, covering topics like rules, certifications, and association details. Answering them manually took up a lot of the support team’s time and slowed down overall operations.
Solution
SCAND delivered a RAG-based AI knowledge assistant within a unified digital ecosystem, combining document search and conversational interaction to provide accurate, real-time answers from multiple data sources.
Key Features
- Advanced AI document search. The system performs deep semantic search across multiple data sources, including internal databases, website content, and documentation repositories, enabling fast and accurate AI document search even within large and unstructured collections.
- Context-aware answer generation. As a RAG-based AI assistant for documentation, the solution retrieves relevant data and generates precise answers based on verified internal content, such as bylaws, regulations, and association data, reducing the risk of outdated or incorrect responses.
- Auto-updated knowledge base. The AI knowledge system automatically updates its knowledge base as new content is added or updated on the platform, ensuring that users always receive up-to-date information without manual data maintenance.
- Conversational AI document assistant interface. The AI document assistant provides a unified conversational interface for interacting with complex documentation, allowing users, members and administrators to quickly access information without navigating multiple systems.
- Integrated enterprise knowledge assistant system. Designed as part of a broader digital ecosystem, the platform integrates with existing infrastructure, supports real-time data synchronization, and scales with growing data volumes and business needs.
Technology Stack
The solution is built on a modern AI stack designed to support a scalable, RAG-based AI assistant, enabling efficient document processing, semantic search, and accurate answer generation.
Frontend
- React (with PWA capabilities)
Backend
- Python
- LangChain
- LangGraph
AI / LLM
- Embedding model
- Open source LLM (Groq)
Data Layer
- Postgres + pgvector
- WordPress
Authentication
- Keycloak (SSO)
Integration
- REST APIs
Related Cases
Core Team
- Solution Architect: Designed the overall system architecture, including the RAG pipeline, data flow, and integration of the AI knowledge assistant within the broader digital ecosystem.
- Backend Developers: Implemented core system logic, built APIs, and ensured seamless integration between the database, website, and AI-powered components.
- AI / ML Engineers: Developed the RAG-based AI knowledge system, optimized information retrieval and response generation, and ensured accuracy of answers based on internal content.
- Frontend Developers: Built the user interface using a React-based architecture, ensuring a consistent user experience across platforms and supporting PWA capabilities.
- DevOps Engineers: Managed system deployment, configuration, and performance, ensuring scalability and reliability of the platform.
- Project Manager: Coordinated the development process, managed timelines, and ensured alignment with business and technical requirements.
Result
The implemented AI knowledge assistant, as part of a unified digital ecosystem, transformed how information is accessed and used across the global organization, improving operational efficiency and reducing reliance on manual processes.
- Reduced support workload through AI automation. The AI support assistant now handles up to 65% of common user and member inquiries, significantly decreasing the burden on support teams and support answers and allowing specialists to focus on more complex tasks.
- Improved efficiency through real-time data synchronization. Automated data updates and system integration reduced administrative overhead by up to 40%, eliminating inconsistencies between platforms and minimizing manual data management.
- Faster access to complex organizational knowledge. Members and administrators can instantly find accurate information related to bylaws, certifications, and association data through a unified AI knowledge system, without navigating multiple systems.
- Enhanced user experience and engagement. A seamless, mobile-friendly digital environment with unified access and AI-powered assistance improved user satisfaction and increased engagement across the platform.