Our customer is a travel company specializing in selling tours and other travel services. Exceptional customer interaction is critical for their success, making high-quality, round-the-clock support a key component of their strategy.
In the competitive travel industry, customers expect fast and reliable service. However, the company faced several challenges that hindered their ability to meet these expectations:
Limited workforce capacity: Insufficient resources to provide 24/7 support due to the high cost and complexity of staffing across multiple time zones.
Manager overload: Peak hours overwhelmed the existing team, leading to delays in responses and reduced customer satisfaction.
Global service coverage gaps: The inability to manage customer inquiries effectively across various time zones limited their reach and service quality.
These issues created inefficiencies in customer support operations and affected the overall customer experience.
To address these challenges, we developed OperAI, an AI-powered Agent for customer support. OperAI is designed to complement, not replace, human agents by enhancing their productivity and enabling efficient, round-the-clock service.
OperAI is an intelligent backend solution that supports customer service teams by automating routine tasks and augmenting the efficiency of human agents. It’s designed to work seamlessly with existing systems and enhance the overall customer support experience.
Real-time assistance: OperAI pre-fills responses or suggests templates, allowing agents to handle inquiries more quickly and effectively.
Automated query handling: The system manages standard customer queries, reducing the workload for human agents.
Scalability and adaptability: OperAI can support multiple time zones, ensuring uninterrupted service with minimal staffing.
Seamless integration: OperAI is built to integrate directly into the client’s existing CRM and communication systems, avoiding the need for major infrastructure changes.
Retrieval-Augmented Generation (RAG) is an advanced AI framework that combines the strengths of retrieval-based and generative models to provide accurate and contextually rich responses. Unlike traditional generative models, which rely solely on pre-trained data, RAG enhances outputs by retrieving relevant information from external knowledge bases or databases in real time. The process involves two key components: a retriever and a generator. The retriever identifies the most relevant documents or data points from a specified source, while the generator uses this retrieved information to craft a coherent and accurate response. This dual-layer architecture ensures that outputs are not only more precise but also grounded in up-to-date information. RAG is particularly effective for applications requiring real-time knowledge access, such as customer support, document summarization, and Q&A systems. By integrating retrieval and generation, RAG reduces hallucination risks, improves response relevance, and enhances the reliability of AI-driven systems.
Shperling's implementation of Retrieval-Augmented Generation (RAG) stands out due to its focus on delivering accuracy, relevance, and scalability for real-world applications. Here’s why it excels:
Shperling’s RAG integrates seamlessly with external knowledge bases, ensuring that responses are informed by the latest and most accurate data. This makes it ideal for industries where up-to-date information is critical, such as customer support.
By combining generative AI with document retrieval, Shperling's RAG minimizes the chances of AI producing inaccurate or irrelevant responses, providing users with trustworthy information.
The system can be tailored to access proprietary databases, manuals, or other domain-specific resources, ensuring that responses are fully aligned with a company’s unique knowledge assets.
Shperling’s RAG is designed to handle large volumes of queries efficiently, making it a robust solution for businesses with high customer support demands.
By leveraging RAG, Shperling delivers responses that are not only accurate but also contextually rich, enhancing customer satisfaction and trust.
OperAI, built on Shperling's RAG framework, is a superior solution for automating routine customer support tasks due to its unique features:
OperAI acts as a co-pilot for customer support teams, assisting agents with pre-filled responses, document lookup, and real-time suggestions. This boosts efficiency without compromising the human touch.
OperAI pulls data from internal knowledge bases, FAQs, and past interactions, ensuring every response is grounded in accurate and context-specific information.
With OperAI, businesses can offer round-the-clock support, handling routine queries even outside standard operating hours, ensuring global customer satisfaction.
By automating repetitive tasks and reducing the workload on human agents, OperAI optimizes resource allocation, cutting costs while maintaining service quality.
Whether handling a few hundred queries or scaling up to millions, OperAI adapts effortlessly to meet demand, making it suitable for businesses of all sizes.
OperAI integrates smoothly with existing CRM and support systems, with configurations tailored to the specific needs of your business.
The implementation of OperAI has delivered transformative outcomes for the client, significantly enhancing their customer support operations:
OperAI has automated repetitive tasks, enabling human agents to dedicate their time to addressing complex customer inquiries. This has increased overall team efficiency and reduced burnout.
With OperAI in place, customer queries are now handled much faster, even during peak hours. The company has consistently maintained swift response times, improving the overall customer experience.
The company now offers consistent, round-the-clock support across all time zones, ensuring that customers receive assistance whenever they need it. This has led to a significant boost in customer satisfaction.
OperAI has streamlined support operations, allowing the company to provide 24/7 coverage with a smaller, more focused team. This has resulted in considerable cost savings while maintaining high service quality.
Shperling takes data security and system adaptability to the next level by deploying large language models (LLMs) directly within the client’s infrastructure. This approach ensures that businesses retain full control over their sensitive information while benefiting from cutting-edge AI technology.
By operating entirely within the client’s network, Shperling ensures that no sensitive data is transmitted or stored outside the organization’s secure environment.
This guarantees compliance with strict data protection regulations such as GDPR, HIPAA, or local industry-specific standards, making it suitable for sectors like healthcare, finance, and travel.
The LLM is trained on the client’s proprietary datasets, such as customer interaction logs, product information, and internal documentation, ensuring highly relevant and accurate responses.
This customization aligns the system with the unique needs of the business, improving both efficiency and user satisfaction.
Shperling’s solution is designed for fast deployment and continuous learning. Updates and new knowledge can be integrated seamlessly, allowing the system to evolve alongside the client’s business.
The in-house deployment model ensures low latency, providing real-time responses even for complex queries, without compromising performance.
The solution enables safe and efficient collaboration between departments, as all data remains within the protected network. This fosters a cohesive workflow without risking data leaks.
By deploying LLMs within the customer’s infrastructure, Shperling combines world-class AI performance with uncompromising data security and adaptability. This approach not only protects sensitive information but also allows businesses to fully leverage AI-powered tools without sacrificing speed or accuracy. It’s a game-changing solution for organizations looking to innovate while prioritizing data privacy and operational efficiency.
This case highlights how OperAI can transform customer support in the travel industry. By working as an AI-powered co-pilot, OperAI enhances agent productivity, ensures round-the-clock service, and optimizes operational efficiency.
Ready to see how OperAI can revolutionize your customer support operations? Contact us today to learn more: