Customer Support

Customer Support Automation with Generative AI

The Challenge

Customer support departments across various industries face numerous challenges in providing efficient and effective assistance to their clients. The diverse range of customer queries, encompassing product troubleshooting, account management, billing inquiries, and general customer care, requires a versatile and responsive solution.

Traditional customer support models, reliant on human operators, often struggle to keep up with the high volume of requests, leading to delayed responses and inconsistent service quality. The need for a scalable, accurate, and fast-responding customer service solution is more critical than ever.

The Solution

Our AI question answering system is designed to meet these challenges head-on, utilizing the latest advancements in Artificial Intelligence, Natural Language Processing (NLP), and Machine Learning. This solution enhances customer support capabilities in several key areas:

  • Advanced Query Understanding: The system uses sophisticated NLP algorithms to deeply understand and categorize customer queries. This understanding allows it to respond accurately to a diverse range of customer needs.
  • Personalized and Contextual Responses: Leveraging the context of previous interactions and customer data, the AI provides responses that are not only accurate but also tailored to each customer's unique situation and history with the company. We created additional context about the client, depending on all data that we have and used it for improving user experience.
  • Real-Time Assistance and Escalation: The AI provides immediate responses to common queries and can intelligently escalate more complex issues to human agents, ensuring that customers always receive the help they need.
  • Feedback and Continuous Improvement: The system is designed to learn from each interaction and customer feedback, continuously improving its accuracy and effectiveness over time. We collect data and feedback from users, and fine-tune it using PEFT\RLHF methods periodically, for fast and sufficient model improving.
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The Framework Is
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The implementation of our AI question-answering system has led to transformative results in customer support efficiency and quality.

Significant Improvement in Response Times

Customers receive instant responses to their queries, drastically reducing wait times and improving overall satisfaction.

Enhanced Customer Experience

With personalized and accurate responses, the system ensures a higher level of customer engagement and satisfaction.

Reduction in Operational Costs

The automation of routine queries and integration across multiple channels leads to significant cost savings in customer support operations.

Continuous Adaptation and Learning

The system's ability to learn from interactions and adapt to changing customer needs ensures that the support quality remains consistently high.



Guillaume Bouchard

CEO at Checkstep

I highly recommend the LyraTech team for their exemplary work at Checkstep where they showcased great expertise in building AI solutions for content moderation systems. They showed a clear proficiency in designing and fine-tuning LLMs, meticulously evaluating 3rd party APIs to flag online harm, and rigorously testing foundational models. Moreover, their ability to iterate on prompts and professionally present their findings to a large audience significantly contributed to advancing our project

Anna Lytvynenko

Co-founder and CCO of Business Logic Group

Our company is a developer of the proprietary ВР2М platform, which is a solution for commercial performance and planning management. To catch momentum from external AI expertise, we invited Lyratech, led by Kateryna Stetsiuk, for a collaborative workshop with our development team. From the very beginning, Kateryna made the discussions engaging. She shared captivating and systematically structured materials, and with her friendly way of explaining complex things, our team quickly got involved in lively talks, looking at real cases from our work. The collaboration with Lyratech brought quick results: our platform unveiled an AI-driven "Talk-to-Data" feature, which empowered the data discovery and decision-making process.
Our cooperation with Lyratech led to the momentum we require!

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