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Air Canada's 5 Lessons Learned: Applying AI and LLM to Customer Service

Air Canada's 5 Lessons Learned: Applying AI and LLM to Customer Service

The rapid integration of Artificial Intelligence (AI) and Large Language Models (LLM) into customer service operations marks a transformative era for businesses across the globe. While these technological advancements promise to revolutionize customer interactions, making them more efficient and personalized, they also come with their share of challenges and learning curves.


In a notable incident that serves as a cautionary tale for businesses adopting AI in customer service, Air Canada faced legal repercussions due to misinformation provided by its AI-powered chatbot. A grieving passenger sought a bereavement fare adjustment based on guidance from the chatbot, which inaccurately stated such fares could be applied for retroactively. This misinformation led to a small claims court case, where the court ruled in favor of the passenger, awarding damages due to what was determined as "negligent misrepresentation" by the airline. This case underscores the importance of ensuring AI systems are accurately programmed and highlights the legal and reputational risks businesses face when AI technology disseminates incorrect information.

From this article, you’ll learn how to:

Lesson 1: The Importance of Accurate Data Retrieval

One of the most critical aspects of implementing AI in customer service is ensuring the accuracy of the data retrieved by the system. This is where Retrieval Augmented Generation (RAG) plays a pivotal role. RAG technology is an innovation improving generic AI LLMs with the ability to provide accurate and relevant responses by intelligently pulling information from a targeted subset of data based on the domain and scope of the inquiry. This approach significantly minimizes the risk of AI "hallucinations," where the system might generate misleading or entirely incorrect information. By leveraging RAG, businesses can ensure their customer service AI applications are reliable and truly beneficial to their users.

Lesson 2: Crafting Your Domain-Specific AI for Precision and Relevance

While generic AI models offer broad capabilities, their performance can be less than optimal when addressing specific industry challenges. Recognizing this, we champion the creation of domain-specific small Large Language Models (sLLM) that resonate with your unique business needs. These models are not just fine-tuned; they are expertly crafted and enriched with your industry’s specific data, jargon, customer interactions, and challenges, ensuring they speak your language, literally.

Creating a domain-specific model with Allganize is a streamlined process that demystifies AI and makes cutting-edge technology accessible to all. Here's how we simplify the journey:

Data Collection and Curation:

While most providers require manual data cleaning and tagging, a laborious task that does not scale well as enterprises add new documents, Allganize works with unstructured data with no manual cleanup or tagging.

We begin by gathering a rich dataset from your domain. This could include technical manuals, customer service logs, product descriptions, and any other relevant information that defines your business landscape. Our team works closely with you to curate this data, ensuring it's high-quality and representative of your domain's complexities and nuances.

Model Training and Fine-Tuning:

Leveraging our proprietary AI technology, we train a Large Language Model specifically for your domain. A user clicks a thumbs up or down button and, if wanted, provides feedback. This process involves adjusting the model's parameters to best reflect the intricacies and specialized knowledge of your industry, ensuring it can accurately understand and respond to industry-specific queries.

Iterative Refinement:

The creation of a domain-specific model is not a one-time effort but a continuous process of learning and improvement. We employ an iterative refinement approach, where the model's performance is constantly evaluated and enhanced based on new data, user feedback, and evolving industry trends. This ensures that the AI remains up-to-date and continues to deliver value.

Simplifying Integration:

To ensure seamless adoption, we provide no-code solutions that allow your teams to easily integrate and manage these AI models within your existing workflows. This means end-users can deploy powerful, domain-specific AI capabilities without needing a team of developers or AI specialists.

By prioritizing domain specificity, we not only enhance the accuracy and relevance of AI-powered interactions but also ensure that your AI investment is deeply aligned with your business objectives. This approach empowers you to offer more personalized, efficient, and insightful customer service, setting you apart in a competitive landscape.

With Allganize, creating and implementing a domain-specific model is not just about leveraging AI; it's about embedding an intelligent, responsive, and continually evolving digital core into your business ecosystem. Let us show you how easy it can be to transform your customer service with AI that understands your domain as well as you do.

Lesson 3: Empowering Data Privacy and Flexibility with Hybrid Deployments

In the evolving landscape of customer service technology, safeguarding sensitive information while harnessing the power of AI is paramount. At Allganize, we understand the critical importance of data privacy and regulatory compliance, which is why we emphasize the value of hybrid deployment models for large language models (LLMs). Hybrid deployments offer the best of both worlds: the robustness and scalability of cloud computing combined with the security and control of on-premise solutions. Here's how we ensure that our hybrid deployments meet your business needs while upholding the highest standards of data privacy:

Customized Data Handling:

Hybrid deployments allow for a tailored approach to data management. Sensitive data can be processed and stored locally, on your own servers, ensuring it never leaves your secure environment. At the same time, less sensitive, anonymized data can be utilized in the cloud for training and enhancing AI models. This dual approach ensures compliance with industry regulations such as ISO27001, HIPAA, or SOC2, while still leveraging cloud capabilities for scalability and performance.

Seamless Integration and Security:

Allganize’s hybrid solutions are designed for seamless integration into your existing IT infrastructure, ensuring a smooth transition and adoption process. We employ state-of-the-art encryption and security protocols both in transit and at rest, providing an additional layer of protection for your data across both environments. This holistic security strategy ensures that your data is safeguarded at every point of the process, from initial input through to AI processing and response generation.

Optimized Performance and Reliability:

Our hybrid deployment model is engineered for high availability and resilience, ensuring your AI-powered customer service functions are always online and responsive. By leveraging local data processing for critical operations and cloud resources for scalability, we ensure that you can maintain optimal service levels even during peak demand or in the face of potential cloud service disruptions.

Continuous Innovation with Compliance:

Hybrid deployments enable your business to stay at the forefront of AI advancements without compromising on data privacy or compliance. We continuously update our models and services with the latest AI innovations, which can be deployed rapidly across the cloud components of the hybrid model. Simultaneously, the integrity and privacy of your on-premise data are preserved, ensuring that your deployment is both cutting-edge and compliant.

Empowered Decision Making:

With Allganize’s hybrid model, you gain deeper insights and retain full control over your AI's learning process and data usage. This empowers your teams to make informed decisions about data privacy, model training, and AI performance tuning, aligning AI operations closely with your business policies and ethical standards.

Allganize's commitment to hybrid deployment models reflects our dedication to providing businesses with powerful, flexible, and secure AI solutions. By choosing a hybrid approach, you ensure that your company's data handling practices are not just compliant, but are also a benchmark for privacy and security in the industry. Let us help you navigate the complexities of deploying AI in a way that respects your data privacy needs while unlocking the transformative potential of AI for your customer service operations.

Lesson 4: Integration with Diverse Knowledge Repositories

Business knowledge is held in multiple systems - from knowledge databases, to local and cloud-based file systems, to messaging apps and email. The effectiveness of AI in customer service is significantly enhanced when the system can integrate with all the various knowledge repositories. This capability ensures that the AI has access to the most current and comprehensive information available, leading to more accurate and helpful customer interactions. However, achieving this level of integration requires careful planning and consideration of both technical and logistical factors. Businesses must ensure that their AI systems can seamlessly connect with different databases and information sources to maximize their utility.

Lesson 5: Simplifying AI Evolution with No-Code Solutions and Community Innovation

In the dynamic landscape of AI, staying agile and continuously enhancing AI capabilities is crucial. Allganize stands out by offering specific functionalities that make these advancements straightforward, even for those without a technical background. Our unique selling points include a no-code AI app creator, an enterprise app market for sharing automations, and a proprietary RAG model that ensures unmatched accuracy. Here's how these features work in tandem to simplify AI management and evolution:

Alli LLM-Enabler:

Our no-code platform empowers every team member to build and deploy custom AI applications. This tool is designed for ease of use, allowing anyone, regardless of their technical expertise, to create AI-driven solutions that automate workflows and enhance efficiency. This democratization of AI application development accelerates innovation and allows your business to quickly adapt to new challenges and opportunities.

Alli LLM App Market

Innovation flourishes in a collaborative environment. Our enterprise app market encourages the sharing of AI-driven automations and applications within your organization. This platform not only promotes a culture of innovation but also speeds up the dissemination of best practices and successful automations across different departments, leveraging the collective intelligence of your workforce to streamline operations and improve customer service.

Proprietary Retrieval Augmented Generation (RAG) Model:

The cornerstone of our AI capabilities is our best-in-class RAG model. This model excels in delivering accurate and relevant responses by continuously learning from new data. It ensures that your AI applications remain at the cutting edge of precision, significantly enhancing the customer experience through timely and accurate information delivery.

Advanced Administration Controls for Data Privacy:

Central to managing AI is ensuring data privacy and security, especially when handling personally identifiable information (PII). Our platform offers sophisticated administration controls that safeguard privacy by automatically scrubbing PII from responses. Furthermore, it provides granular permission settings, allowing you to define access levels based on documents, folders, users, and workgroups. This ensures that sensitive information is protected and that access is precisely controlled, aligning with your organization’s data governance policies.

Taking the Next Step

The journey to integrating AI and LLM into customer service is fraught with challenges but also ripe with opportunities for businesses willing to navigate these waters carefully. By prioritizing accurate data retrieval, domain-specific knowledge, data privacy, seamless integration with diverse knowledge sources, and continuous learning and adaptation, companies can harness the full potential of AI to enhance their customer service operations.

Allganize focuses on delivering the tools and technologies businesses need to overcome these challenges and deliver on the promise of AI in their specific context, processes, teams and customers. Allganize’s proprietary best-in-class RAG, domain-specific LLMs, data privacy- and security-driven deployment models, and no-code administration have already enabled hundreds of enterprise customers to improve their service levels while reducing operating costs. 

To find out how you can be successful with AI and see what Allganize can do for you, contact us here.