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What to Consider When Choosing a Generative AI Solution for Your Enterprise?
Enterprises must consider many factors before offering generative AI (GenAI)-based applications to their customers. The points to consider come together at this point: Can solutions specific to an enterprise’s identity, policies and, most importantly, customers be developed using large language models based on general, unverified data available on the internet?
After OpenAI's ChatGPT was introduced to the world in October 2022, decision-makers in organizations began looking for ways to deliver the “human-like response to everything” experience that ChatGPT provided, primarily in their customer service channels. In a relatively short time, service providers offering AI-based conversational solutions began marketing products that claimed to meet this demand. Shortly thereafter, infamous stories of GenAI-powered virtual customer agents began to go viral on social media. Abandoning large language models was not an option, so where was the solution?
Although GenAI is fun and helpful for individual use, when employed under a corporate identity, the magic-like face of this technology can turn into a disruptive feature in corporate communication. In fact, this is the “generative” side of the business, the magic-like aspect. Producing answers according to the language model occurs independently of content and meaning, which can sometimes lead to erroneous content production, known as hallucination. Although this may seem like a software defect at first glance, it stems from the difference between discussing a certain topic with anyone and discussing it with an expert on that topic.
Let’s think about it this way: Let’s say you have a question about banking. You want to make the best use of your investment. You wouldn’t ask the first person you see your questions, would you? What about your doctor? If your doctor did not make their fortune from money management and only earned it from their profession, you probably wouldn’t ask them. Yet, would you hesitate to ask a banker or an investment expert? Wouldn't it be best to consult your own investment advisor, who knows your risk tolerance and the appropriate investment instruments?
In this example, even if we assume that each of the individuals mentioned, the doctor, the banker, and the private investment consultant, are knowledgeable, the trust we will have in each of them will be different. When it comes to large language models, it would not be wrong to think that the dataset they refer to is everyone who has left a mark on the Internet. What should not be overlooked here is that the answer produced is produced according to the language model, not the content and accuracy. So, if the grammatical structure of the answer sentence is correct, then it’s assumed that the language model is working correctly. In fact, the success of the first-generation large language models was defined in this way. Though new generation large language models, which are coming into use at a dizzying pace, capture the context of the subject much better than their predecessors. However, it is still useful to be cautious about using such a solution under a corporate identity because a mistake can cause health, financial, trust, ethical and legal losses.
This fact does not tell organizations to give up on GenAI, but to choose their solution partners more carefully. So, what criteria should organizations use to choose their partners who will provide GenAI solutions that will make them strategically and financially superior?
Technical Qualification
It is becoming more and more difficult to keep up with the GenAI developments in technology. While decision makers in enterprises are happy to be surrounded by a multitude of options, it is important to pay attention to the fact that the solution provider is not a follower of technology, but a producer, which is one of the main factors that makes a difference among this diversity.
SESTEK's R&D unit develops proprietary natural language understanding models, as well as continuously analyzing and testing state-of-the-art wide-ranging language models, adapting them to GenAI- based SESTEK products to meet the needs of corporate customers. In addition, SESTEK's offerings with SaaS model ensure that applications are always at the service of organizations with the most up-to-date versions without compromising business continuity.
Security and Compliance
The main factors that slow down the implementation of GenAI applications in enterprises are the sensitivities regarding compliance and information security. The principles regarding the processing of enterprise and customer information by large language model-based applications are controlled by regional and country regulations. It is also a known fact that enterprises try to be extremely careful not to create a lack of trust in their customers while serving them. For this reason, it is necessary to pay attention to how a company providing GenAI- based solutions addresses these issues and how enterprises reflect such sensitivities in their product development policies.
With the gains of its 25 years of corporate experience, SESTEK has adopted the principle of adding the necessary developments for security and compliance to its product roadmaps with high priority by embracing the responsibilities of corporates towards their customers. SESTEK products have ISO 27001, ISO 9001 and SOC 2 Type 2 certificates and are KVKK, GDPR, HIPAA compliant. The Compliance Office within SESTEK not only transfers the understanding of secure software development and ethical responsibility to product development teams but also guides the relevant units in SESTEK to carry out the application, consultancy, and sales processes with the same awareness. As a result of this understanding, SESTEK GenAI applications always use RAG techniques and personally identifiable data (PII) is always censored.
Requirement Analysis
An organization's business area, goals and customer expectations shape the organization's needs. In the analysis of requests and needs, a solution provider who understands the organization's goals and pain points, has references in the business field and has completed similar projects will be seen as a reliable business partner, not just a product seller.
In order to speed up the customer service processes in the sectors of banking, finance, insurance, communication, call center, e-commerce, health, etc. and to make their lives easier, SESTEK understands what they need and what problems they need to solve by constantly working with its customers before and after sales and customizes its products according to the needs of its customers. To get the maximum efficiency from GenAI applications and see the return on investment in a short time, determining the right use case scenarios is of critical importance. For this reason, SESTEK's expert consultants work in full cooperation with the authorities in the enterprise before and after sales to determine which solution is suitable and how it should be adapted according to expectations and priorities.
Ease of Use
SESTEK's GenAI solutions perform different functions such as summarizing and classifying call center conversations and designing the dialogues of virtual customer agents in self-service channels, while the ergonomics of the users are considered in the forefront in the design of the applications. You can read SESTEK's application development principles in another blog post.
Opportunity to Try and See
It is a fact that the most effective way to eliminate the hesitations that make it difficult for enterprises to make decisions and prolong the purchasing process is to experience the evaluated solution instead of explaining it on slides. SESTEK's flexible sales models, which include "try and buy" or small-scale pilot application development, are ideal for deciding on the most suitable GenAI solution for your enterprise. Thus, RAG-supported GenAI application is shaped according to your enterprise’s policies and preferences and the business goals are achieved.
In Conclusion
The priorities and sensitivities of enterprises and industries may be similar, but they differ. The way to provide customized solutions supported by a wide range of language models is to know the business domain as well as to be proficient in technology. For 25 years, SESTEK has been a reliable business partner for enterprises to transform their self-service channels from DTMF IVR solutions to rule-based virtual customer agents and AI based virtual customer agents. Today, SESTEK continues to apply the experience gained by over 500 customers to its own R&D-based technology on GenAI - supported solutions built around large language models.
Author: Buğra Şamlı, Presales Director
