AI agent with RAG for instant customer service intelligence
Empowering support teams with an autonomous AI agent that retrieves and processes customer data in real-time.
DBF
DBF sought to modernise their customer support operations by implementing an intelligent interface capable of navigating complex internal datasets. The goal was to provide support staff with a tool that could instantly retrieve accurate customer information and policy details to resolve enquiries faster.
Support agents were manually searching through multiple disconnected databases and documentation silos to answer customer queries. This led to long wait times, inconsistent answers, and high cognitive load for the staff. The existing knowledge management system lacked a unified search layer, making it difficult to extract specific insights during live customer interactions.
What SevenLab built
SevenLab developed a sophisticated AI agent using Retrieval-Augmented Generation (RAG) to bridge the gap between raw data and actionable answers. This system indexes DBF's internal documentation and customer records, allowing the agent to provide context-aware responses through a simple chat interface.
RAG architecture
Retrieves real-time information from internal documents to ensure AI responses are grounded in fact.
Intelligent chat interface
A natural language interface that allows staff to query complex data as if speaking to a colleague.
Secure data integration
Seamless connection to existing customer databases while maintaining strict data privacy protocols.
Instant response engine
Reduces the time spent on manual research from minutes to milliseconds per query.
Measurable business impact
The implementation of the AI agent transformed DBF's support desk into a high-efficiency operation. By automating the information retrieval process, the team achieved a significant reduction in average handle time while increasing the accuracy of the information provided to customers.
The RAG-based agent has completely changed how our team works. Instead of digging through files, they get the right answer in seconds, allowing them to focus entirely on the customer experience.
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