The flood of ever-new LLMs (Large Language Models) or AI-based systems that can be used in customer service leaves many companies speechless and confused. Various approaches and models, data protection issues, and integration capabilities into the existing system landscape can overwhelm businesses. The realization that a single AI platform cannot meet all requirements means that companies need a well-thought-out AI strategy to avoid getting lost in the jungle of complexity and possibilities. When companies use multiple LLMs and AI-based systems depending on the application, central orchestration is needed: this is where AI gateways come into play.
What exactly are AI Gateways?
AI gateways will play a key role in practical implementation. AI methods demonstrate their strengths and weaknesses in various areas, highlighting their significant impact on daily life, future autonomous machines, language algorithms, healthcare, urban planning, regulation and governance, ecological effects, and the arts. AI gateway technology promises not only to fundamentally change how companies operate but also to facilitate their integration into existing systems and open up new possibilities for data protection and security.
AI gateways offer an innovative solution to make AI applications more flexible, reliable, and scalable. They are a specialized type of API gateway that focuses on managing and securing communication between applications and AI models. They provide a central platform that allows companies to access a variety of AI models, such as LLMs, without having to worry about the complexity of each model.
Easy integration and management
AI gateways simplify the integration and development process by providing a standardized interface for accessing various AI models and services. They also support the management of security requirements, such as authentication and authorization, to ensure that only authorized applications can access AI models. Additionally, AI gateways can enhance security through features like authentication, authorization, rate-limiting, and comprehensive API lifecycle governance. They offer centralized monitoring and management of AI traffic, allowing for the oversight of data usage and ensuring compliance with internal standards.
Orchestration and data protection: AI gateways offer many advantages
AI gateways significantly reduce the effort required to integrate AI services into existing systems and applications. They provide a unified interface for managing and orchestrating AI services, simplifying the architecture and enabling centralized control of AI usage. This simplification also translates into substantial cost savings. In the future, companies will be able to choose from an ever-growing number of models and AI services, and they will have to. There will be no "one AI size fits all." Specialized AI services and platforms for specific industries and applications will ensure that individual requirements are met. The level of specialization will continue to increase, and smaller models (SLMs, Small Language Models) will gain popularity due to their faster adaptability and lower training requirements.
Regardless of whether a company uses only one or multiple models and how many AI services are in use, central orchestration through an AI gateway is essential.
The benefits of AI gateways also extend to simplified AI usage for developers, centralized control of AI traffic, and cost optimization through AI traffic analysis. The VIER AI Gateway, in particular, stands out by helping companies implement AI solutions in a compliant and cost-effective manner, adhering to internal KPIs, compliance, and governance rules. Data protection, operating agreements, the EU AI Act, or industry-specific requirements, such as those in banking or healthcare, are pitfalls that can have significant impacts on a company. For example, with the VIER Privacy Manager, data from customer inquiries can be anonymized and pseudonymized. As a result, customer-specific data does not flow back into a foreign-hosted LLM system for training purposes.
Practical applications of AI gateways
In practice, AI gateways find diverse applications, particularly in complex environments. Whether in marketing, sales, customer service, or contact centers, companies everywhere are grappling with complexity. Customer journeys now encompass many more touchpoints than in previous years. This results in a dangerous mix for companies: both contact volume and average handling time are rising rapidly. It is becoming harder for both customers and service teams to navigate quickly. Given the simultaneous shortage of skilled workers, this situation can easily become toxic. AI in all its facets will play a crucial role in alleviating this situation, whether as a standalone, autonomous component in a chatbot or as an intelligent assistant. Only companies that adopt a strategic AI approach and employ the key component for secure orchestration – AI gateways – will be able to fully realize the potential of AI applications.
Benefits in Everyday Work
The benefits of AI gateways for businesses manifest in various ways, ranging from automating business processes to enhancing interactions with customers.
Automation and efficiency boost through process automation: Companies utilize AI gateways in conjunction with AI-powered marketing automation, chatbots, or voice bots to automate business processes and repetitive tasks, especially in customer service, freeing up employee resources for value-added tasks.
Deeper insights through data analysis: Companies gain deeper insights through AI-powered customer analytics of large datasets, enabling them to optimize business processes, marketing strategies, and customer journeys. Here again, the use of AI gateways is a prerequisite for effectively linking various services and LLMs.
Security and customer relationships: By personalizing the customer experience, AI gateways contribute to building stronger customer relationships. However, this is only based on current information, excluding hallucinations. Depending on the use case, this requires different AI services, LLMs, and AI-powered applications such as marketing automation or conversational automation. Orchestrating is the crucial component for generating current, accurate, and relevant information for customers. For customer service or contact centers, tailored, company-specific responses to customers are a knockout criterion. With RAG, the efficiency of LLM applications (Large Language Model) can be improved by using company-specific data. For this purpose, data and/or documents relevant to a customer inquiry are retrieved and made available to the employee or a chatbot. RAG is another AI service that needs to be orchestrated.
These aspects demonstrate that AI gateways not only significantly improve the efficiency and security of business processes but also provide innovative solutions for the challenges of digital transformation and elevate customer interaction to a new level. By implementing API gateways, companies can establish a robust, secure, and high-performance infrastructure that enables seamless integration and reliable data exchange between various platforms and systems. This technology thus constitutes a crucial building block for digital transformation and securing future business success.
Opportunities and future developments
The development and implementation of AI systems are at the heart of a rapidly evolving technological landscape, where the combination of human skills and AI strengths must be seen as key to improved outcomes. However, this requires not only technological adaptation but also a cultural shift within organizations. This necessitates a growth mindset and the establishment of ethical guidelines for collaboration between humans and AI.
Conclusion and outlook
The consideration of the diverse applications, advantages, and challenges of AI Gateways paints a comprehensive picture of their significance in the digital landscape. Their influence ranges from optimizing business processes and improving security standards to enabling innovative use cases, underscoring their integrative role in existing and future systems. These technologies not only provide solutions for current demands but also open new horizons for the development and implementation of forward-looking digital infrastructures.
In terms of data protection and security, AI Gateways represent a critical aspect for companies that requires careful consideration and integrated management strategies. The associated challenges, particularly regarding corporate responsibility, highlight the need for ongoing research and development in this area. Consequently, it is essential for companies, developers, and users from specialized departments to collaborate in order to fully understand and utilize the potentials and limitations of AI Gateways. This will ultimately pave the way for a responsible digital future.
Must haves! High availability and reliability
By centrally managing models and requests, an AI Gateway increases the availability and reliability of AI services within the company and saves costs. Ultimately, it's about optimizing the efficiency of all deployed AI initiatives.
Must haves! Context sensitivity and personalization
AI Gateways enable finer control of interactions with LLMs by considering context and user preferences, leading to personalized, relevant responses. This is a top priority for those responsible for Customer Experience. Delivering personalized content at the right time and at the relevant touchpoint necessarily requires an orchestration layer.
