Generative AI Customer Service:
Resources for Technical Teams

Generative AI (GenAI) and Large Language Models (LLMs) have immense potential to significantly improve the performance, efficacy, and customization of interactivity between customers and businesses to change the way customer service is performed and managed. These state-of-the-art AI technologies are not merely iterative upgrades. They represent a fundamental change in how businesses can engage with their customers and address their queries. In fact, GenAI and LLMs together form a new category called “Agentic AI”, a type of artificial intelligence that can think and act on its own to achieve specific goals, instead of following preset instructions. These systems are designed to feel more “independent” and can interact with people in a way that feels natural, like having a conversation or using other forms of communication.

Generative AI customer service promises.

Unprecedented performance and efficiency.

Implementing Generative AI customer service by using LLMs can result in a marked increase in response times. These AI-enabled systems can process and comprehend customer inquiries much faster than human agents, providing swift responses to a wide range of questions. This enhanced speed compared to human agents translates to minimized wait times for customers and increased efficiency for support teams.

Further, AI-driven systems can manage unlimited customer interactions simultaneously, effectively eradicating queue times and ensuring immediate attention to every customer. This functionality allows businesses to scale their customer service operations without a proportional increase in their workforce, leading to significant cost savings and improved customer satisfaction.

Personalized customer experiences throughout the customer journey.

Generative AI and LLMs are exceptionally proficient at understanding the context and subtlety in language, enabling them to provide highly customized responses to customer inquiries throughout customer journeys—including pre- and post-sales. By analyzing extensive data and learning from previous interactions, these AI systems can adapt their communication style and content to align with individual customer preferences and needs—all while matching a brand’s voice and tone.

This heightened level of customization extends beyond merely addressing customers by name. AI-powered customer service can recall past interactions, anticipate customer needs, read and write information from external systems like CRMs, knowledge bases, and more—and offer proactive solutions, creating a truly personalized experience that promotes customer loyalty and satisfaction.

24/7 availability and consistency.

Unlike human agents, AI-powered customer service systems can operate around the clock without fatigue or breaks. Constant availability ensures that customers can receive support whenever needed, regardless of time zones or holidays.

The consistency in service quality is another significant advantage, as AI systems maintain the same level of knowledge and politeness throughout all interactions, eliminating the variability that can occur with human agents.

Multilingual support.

Large Language Models possess the remarkable ability to comprehend and generate text in multiple languages. This feature enables businesses to offer seamless multilingual support without requiring separate teams for each language. As a result, businesses can expand their global reach and provide consistent high-quality customer service to a diverse, international customer base.

 Gain insights so you can iteratively improve CX.

You can use generative AI agents to review all customer interactions and provide feedback on them. This allows you to get new insight into your customer conversations, identify areas for improvement, and pinpoint trends and topics—so you can continually improve your CX.

Generative AI customer service challenges to implementation.

But for all the excitement and promises that generative AI customer service holds, there are major challenges that operations and technical teams face. Let’s look at them one by one.

Compliance, data privacy & governance concerns in Europe.

When deploying generative AI for customer service in Europe, GDPR Compliance and data sovereignty are key considerations. You must fully comply with GDPR requirements for data collection, processing, and storage. You must also ensure that data is stored within the EU/EEA or on EU-approved cloud infrastructure to align with data sovereignty laws.

Critical enterprise scale and compatibility considerations:

• API and System Compatibility: You want an easy integration model for key systems and AI layers.
• AI Governance Compliance: You must maintain observability and compliance with whatever AI layer you are building. If buying your solution, ensure your vendor does not duplicate their efforts or architecture.
• Customization and Flexibility: While templates and “accelerators” are important, your chosen solution, whether built or bought, should be customizable and offer flexibility—like the ability to choose from a range of LLM models, including your own in-house or proprietary models, and leverage them how you see fit.
• Scalability Across Regions: Your chosen solution should be scalable and able to handle regional variations while maintaining performance.
• Latency and Performance: Especially when “real-time” interactions are required, you need a solution with low-latency performance to avoid lag—and the tools required to debug, test your experience, and improve performance over time.

Compliance, data privacy and governance at Quiq.

Quiq delivers enterprise-grade generative AI with industry-leading security, compliance, and governance capabilities built for global operations—including SOC-II certification. Our platform maintains strict GDPR compliance with dedicated EU data centers in Frankfurt and Stockholm, ensuring data sovereignty and providing comprehensive compliance tools for Subject Access Requests (SAR) and Right to Be Forgotten (RTBF) requirements.

Purpose-built for enterprise scale, Quiq offers flexible deployment options including BYO-LLM capabilities, extensive API integrations, and proven connectivity with leading enterprise systems from CRM to knowledge management platforms like Confluence and Shelf. Our architecture supports granular permission controls and robust AI governance, while delivering consistent sub-second latency across global regions.

With localized support in multiple languages and dialects, regional training resources, and customizable workflows that adapt to local regulatory requirements, including German Workers Councils, Quiq enables enterprises to confidently deploy conversational AI that meets the highest standards of security, performance and compliance.

Balance generative AI for customer service with AI Studio.

We created AI Studio so you can add agentic AI to your customer experiences. It can leverage any AI governance, processes and gateways that you may be building. While we have built-in support for a variety of language models, our custom adapters can take advantage of your custom models and gateways for times when you require all language model interactions to be routed via a central gateway layer.

Traditional software development follows a deterministic, linear process: build, test, deploy, and measure. However, generative AI introduces a new paradigm, especially where it is exposed to your customers. Traditional chatbot and AI automation tools—which often bolt generative AI/LLMs onto a Gen 1 platform—fail to consider the non-deterministic nature of GenAI.

Quiq’s AI Studio was created for builders to create safe, customer facing AI applications. It takes an “open book” approach, where nothing is hidden. AI Studio provides full visibility of every LLM interaction, from the prompts sent to the completions returned.

Want to change a prompt or even swap one LLM out for another? No problem. AI Studio allows you to do that at an individual prompt level, and then compare the results side by side, replaying and tweaking as much as you’d like before setting your changes live.

Quiq’s expertise and solution is built for AI in CX, enabling technical and non-technical team members alike to build faster and more confidently. We understand that customer facing AI must be an extension of your brand.

AI Studio provides a flexible toolkit to ensure you’re only answering in a brand-approved, accurate manner. From our AI resources toolkit—which empowers you to transform, sync, and prep your data for use by your AI agent—to our flexible building tool, which enables you to combine rigorous prompt chaining and prompt parallelization with business logic to ensure you’re identifying inaccurate answers before they’re sent, and handling out of scope inquiries before you generate a response.

In summary, Quiq can integrate with or leverage the AI governance layer you’re building, while providing a deep and robust toolkit for your customer-facing functions to build faster and safer.

AI tech talks.

Join Kyle McIntyre, Head of AI Engineering at Quiq, for a comprehensive explanation of Generative AI and Transformers – the groundbreaking techniques that enable Large Language Models to read and generate language with unprecedented accuracy and fluency.

These sessions are designed to provide you with an even deeper understanding of:

• The architecture of Transformer models
• Training processes for Large Language Models
• Fine-tuning techniques for specific applications
• Retrieval Augmented Generation (RAG)