CASE STUDY
Global Leader in
Management Consulting
Transforming Data Into
Actionable Insights With
AI-Powered Solutions
Project Overview
Distillery worked with the client to deliver AI-driven solutions to transform knowledge
management and user support processes for two distinct use cases: a guest contact center
and a television network. The aim was to deliver accurate, context-aware responses while optimizing backend systems and ensuring eicient scalability.
Project in Numbers
- Developed and deployed 2 AI-driven platforms tailored to client needs
- 80-120% growth in active user engagement for the TV network
- Optimized response times to under 1.5 seconds for complex queries
Project Overview
Distillery worked with the client to deliver AI-driven solutions to transform knowledge management and user support processes for two distinct use cases: a guest contact center
and a television network. The aim was to deliver accurate, context-aware responses while optimizing backend systems and ensuring eicient scalability.
Project in Numbers
- Developed and deployed 2 AI-driven platforms tailored to client needs
- 80-120% growth in active user engagement for the TV network
- Optimized response times to under 1.5 seconds for complex queries
Team
Challenges Faced
The client faced significant challenges in managing vast amounts of unstructured and structured data across their operations. They needed to surface relevant knowledge quickly and accurately for internal teams and users, ensuring seamless access to information from extensive repositories like wikis and SharePoint. Additionally, extracting and structuring metadata from raw video content posed technical hurdles, particularly for creating personalized user experiences. Scalability was another pressing concern, as the systems needed to handle growing data volumes eiciently while maintaining cost-eectiveness and minimizing downtime during updates. These challenges required innovative AI-driven solutions to optimize knowledge retrieval, improve engagement, and ensure operational reliability.
Challenges Faced
The client faced significant challenges in managing vast amounts of unstructured and structured data across their operations. They needed to surface relevant knowledge quickly and accurately for internal teams and users, ensuring seamless access to information from extensive repositories like wikis and SharePoint. Additionally, extracting and structuring metadata from raw video content posed technical hurdles, particularly for creating personalized user experiences. Scalability was another pressing concern, as the systems needed to handle growing data volumes eiciently while maintaining cost-eectiveness and minimizing downtime during updates. These challenges required innovative AI-driven solutions to optimize knowledge retrieval, improve engagement, and ensure operational reliability.
Solutions Implemented
Our team at Distillery collaborated closely with the client to deliver robust solutions:
AI-Driven Knowledge Retrieval:
- Created a retrieval-augmented generation (RAG) system to ensure accurate, traceable responses.
- Leveraged Python, FastAPI, and OpenAI APIs to handle AI-based data analysis and response generation.
- Built a robust backend using PostgreSQL (PgVector) to manage embeddings and vectorized queries.
Video Content Metadata Automation:
- Conducted video analysis to create structured metadata from raw episodes, capturing details like actors, scenarios, and other contextual elements.
- Enabled metadata-driven personalization for TV network users.
Personalized User Engagement:
- Delivered personalized content based on user preferences and historical data.
- Integrated AI-generated imagery and contextual recommendations for enhanced engagement on digital platforms.
Efficient Development Practices:
- Adopted iterative testing and benchmarking using tools like Uptrain AI to ensure model accuracy and quality.
- Optimized response times to achieve near-real-time outputs (~1400 milliseconds).
Outcomes Achieved
The solutions delivered significantly improved knowledge management and personalization capabilities. The guest contact center benefited from accurate, real-time support powered by AI, enhancing user satisfaction and operational eiciency. The TV network achieved automated metadata generation, enabling personalized user experiences and deeper engagement with their content. Scalability and adaptability of the platforms ensured seamless handling of growing data volumes and evolving user needs.
Outcomes Achieved
The solutions delivered significantly improved knowledge management and personalization capabilities. The guest
contact center benefited from accurate, real-time support powered by AI, enhancing user satisfaction and operational
eiciency. The TV network achieved automated metadata generation, enabling personalized user experiences and deeper engagement with their content. Scalability
and adaptability of the platforms ensured seamless handling of growing data volumes and evolving user needs.
Technologies
What’s Next
The teams will focus on further optimizing AI models for cost eiciency and accuracy, while exploring new integrations for advanced data analytics and user engagement features. The long-term goal is to replicate and adapt these solutions across additional domains, expanding their impact and utility.
About the Client
A global leader in management consulting, known for driving innovation and delivering measurable results. They specialize in helping businesses solve their most complex challenges, from strategy and operations to technology and digital transformation. They empower organizations to achieve sustainable growth and outperform competitors.