Are you still spending countless hours manually reviewing Call Center recordings to assess agent performance? It's time to step into the future with the AI Quality Assurance solution from Visor.ai. Powered by cutting-edge artificial intelligence, this innovative solution automates the entire call auditing process, enabling you to evaluate every single Call Center interaction based on your specific criteria — all with unparalleled efficiency.

With AI Quality Assurance, every call can be thoroughly analyzed, ensuring a comprehensive and unbiased performance evaluation of all agent interactions. It’s all done with precision and consistency. Say goodbye to manual evaluations and embrace an automated solution that empowers you to enhance Call Center performance and deliver superior customer experiences.

AI Quality Assurance

AI Quality Assurance is a groundbreaking tool for automating the Call Center audit process. Designed to be flexible and modular, it can be easily customized through an intuitive, user-friendly interface, requiring no technical expertise. At its core, this innovative tool leverages advanced Speech-to-Text (STT) models and cutting-edge Large Language Models (LLM) to ensure agent performance evaluations are conducted with exceptional accuracy.

In addition to conducting detailed agent performance evaluations, AI Quality Assurance can be customized to extract valuable business insights from each call, such as call summarization, topic classification, and even sentiment analysis. These insights offer a deeper understanding of the overall Call Center experience and can then be used to enhance Call Center performance and strengthen customer relationships.

The technology’s ability to process long audio files in minutes and handle large volumes of data streamlines the entire auditing process. With this solution, Call Center evaluators can quickly access agent performance evaluation for recent calls, significantly reducing the workload of manual evaluation. This allows evaluators to focus on higher-value tasks, ultimately boosting productivity and improving service quality.

Conclusion

AI Quality Assurance from Visor.ai is not just a tool — it’s a strategic asset for any Call Center operations. By automating agent performance evaluations and providing rich, actionable insights, it enables you to maintain consistent quality, optimize agent productivity, and elevate the overall customer experience. Move beyond manual audits and unlock the full potential of Visor.ai technology. To learn more about this feature and how it can enhance your business, contact our team.

João Granja
Senior Data Scientist

Large Language Models (LLMs) have revolutionized the AI landscape, pushing the boundaries of what’s possible by generating human-like content with incredible precision and quality. However, while these models have shown impressive capabilities, there are some challenges when maintaining up-to-date knowledge and handling domain-specific topics.

The Power and Limitations of LLMs

LLMs are pre-trained on large text datasets, allowing them to learn the intricacies of linguistics, such as syntax and semantics.

Despite this impressive training, LLMs often face limitations due to the broad nature of their knowledge base, which can become outdated in the fast-moving world of today. When it comes to complex and specialized domains, LLMs can produce “hallucinations” — false, inaccurate, or nonfactual information that might seem plausible but lacks authenticity.

The Role of Retrieval-Augmented Generation (RAG)

To overcome these limitations and enhance the performance of LLMs, a solution called Retrieval-Augmented Generation (RAG) has emerged. This technique improves LLMs' ability to generate accurate and contextually relevant information by integrating external sources of knowledge.

RAG empowers LLMs to access up-to-date information, providing a mechanism to generate responses that are not only human-like but also aligned with the latest facts and specific to the domain in question.

Visor.ai’s Gen.AI Uploader

Visor.ai has leveraged the power of RAG by introducing the GenAI Uploader, a user-friendly feature that enables our clients to enhance the performance of LLMs in their specific industries. By allowing users to upload important external documents such as PDFs, URLs, or DOCX files, the GenAI Uploader integrates these tailored datasets with the generative power of LLMs.

With GenAI Uploader, our clients unlock the power to customize RAG's behavior and responses, minimizing “hallucinations” and ensuring accurate interactions. What sets Visor.ai apart is our ability to make use of LLMs and RAG performances to deliver a fully tailored and trustworthy answer.

How Does It Work?

With an intuitive dashboard, clients can easily upload domain-specific content to ensure the AI uses relevant and current information. This integration helps avoid the pitfalls of outdated or generalized knowledge and ensures that the AI can address more complex, specialized topics with greater precision.

Conclusion

The Gen.AI Uploader represents a leap forward in AI technology, combining the extensive capabilities of LLMs with the power of the Retrieval-Augmented Generation. By empowering users to input specific, up-to-date knowledge, Visor.ai provides a tailored, high-performance solution that helps businesses solve complex problems with confidence and accuracy. Contact our team and discover how Gen.AI Uploader can transform your business.