Baking AI into your apps

For data science and engineering teams, the last few months have witnessed generative AI implementations taking center stage, disrupting established roadmaps. Despite facing budget constraints in 2022, the introduction of ChatGPT spurred a 94% increase in AI spending for businesses in 2023.

This wave has also led to the rise of off-the-shelf large language model (LLM) apps readily available for various industries and use cases, from support chatbots to applications for CRM automation. However, amidst the convenience they offer, the question arises: can these off-the-shelf solutions fully address the unique needs of your business? Building your own bespoke LLM application which integrates your custom data into a pipeline that uses an LLM, like the one offered by OpenAI or other providers, might be a compelling alternative that’s tailored to the needs of your business.

Here's a look at why it's a choice worth considering.

Every business is unique, with its own set of challenges, goals, and operational processes. Off-the-shelf LLM solutions are designed to cater to a broad range of industries and use cases. They may not align perfectly with your specific requirements. For example, some off-the-shelf support chatbots can read public data, but can’t read text from more custom sources such as Confluence and internal wikis or connect to your data lake or warehouse. You might also have difficulty adding business logic or trying out different LLMs.

Custom LLM applications can be trained on a dataset that is relevant to your business. You can tailor the application to work seamlessly with your existing systems, processes, and data. This allows you to precisely address your business's unique needs leading to more accurate and relevant results.

For instance, if you're in the banking industry, a custom LLM application can streamline loan application processing. It can connect to and evaluate applicants' financial information, credit histories, and collateral to generate comprehensive reports, helping your bank make informed lending decisions efficiently. You could also build a custom LLM application to generate customized financial reports for clients, incorporating specific investment strategies, risk profiles, and goals. This ensures that the generated reports are relevant to your clients' financial objectives.

Whether it's automating customer support responses, content generation, or data analysis, a custom LLM solution can be fine-tuned to work more efficiently based on your processes. You can find and implement every opportunity to increase efficiency instead of settling for the more popular and broad ones offered by off-the-shelf applications that warrant a market for a product. This saves time as well as reduces the margin of error in tasks by being more relevant.

For example, a custom application can be designed to handle customer support inquiries through chatbots powered by LLMs. These chatbots can be trained on your specific products or services and past interactions to provide instant, accurate responses to common queries, improving customer satisfaction and freeing up human support agents for more complex issues.

You can build a custom LLM application such that it seamlessly integrates into your existing technology stack. You can design it to communicate with other software, databases, and tools your organization uses, creating a cohesive ecosystem. This integration ensures that your LLM application works harmoniously with your other systems, facilitating data flow and accessibility.

For example, in retail, a custom LLM application can integrate with your CRM system to enhance customer profiles, allowing for more effective loyalty program management and personalized marketing campaigns.

With AI use becoming more widespread, managing regulatory risks and ensuring data security is increasingly significant. When you decide to use an off-the-shelf LLM application, it means you are trusting it to keep sensitive information safe. The responsibility is on your shoulders to be thorough, read all the details, ask important questions like will the vendor treat private data as carefully as your organization does, and make sure that your choice is right.

A custom LLM application can be deployed on-premises giving you much greater control over data security and privacy measures. You can implement solid encryption, access control, and compliance with industry-specific regulations, ensuring that your data remains secure and in compliance with relevant laws.

As your business grows, so do your requirements. Off-the-shelf LLM solutions may not be scalable enough to accommodate your expanding needs. Custom applications, on the other hand, can be designed with scalability factored in. You can easily integrate new features and functionalities as your business evolves, without having to overhaul your entire system.

For instance, in marketing, a custom LLM application can continuously optimize advertising campaigns, adjusting keywords, targeting, and content to accommodate growth while maintaining efficiency.

A custom LLM application can provide you with unique capabilities and features that set you apart from others in your industry, attracting more customers who are looking for advanced solutions.

For example, if you're in the healthcare sector, a custom LLM application can analyze medical literature and patient records to offer personalized treatment recommendations, giving your organization a significant advantage. In retail, a custom LLM application can predict demand trends and optimize inventory levels, ensuring that you always have the right products in stock to meet customer demands efficiently.

While building a custom LLM application may require a significant initial investment, it often proves to be more cost-effective in the long run. Off-the-shelf solutions come with licensing fees, which can accumulate over time.

Custom LLM applications can be built with future updates and advancements in mind. This means that you can adapt to new technologies and trends more easily, ensuring your business remains relevant in an ever-changing market.

For instance, in e-commerce, a custom LLM application can continuously adapt newer recommendation algorithms to incorporate emerging trends and customer preferences, ensuring your business remains relevant in an ever-changing market. A custom LLM application can continuously optimize supply chain operations by adapting to emerging trends, market dynamics, and customer preferences, ensuring your business remains relevant in an ever-changing market.

Undoubtedly, building custom LLM applications also comes with its own challenges such as the need for huge amounts of data, teams with specialized skill sets, and substantial time and financial investments. They are also harder to update and maintain. However, there are platforms available today that make it much easier to combine your own data with an LLM and build an application to solve custom challenges. They let you access any LLM provider, create applications and workflows using either a visual interface or coding, and securely deploy them for use. You can iterate rapidly, make the most of various LLMs, connect to your databases and systems, and build in custom business logic and prompts securely. Data experts can develop use cases within a few hours for business teams who can in turn provide feedback to improve the quality over time.

Such platforms help you blend the speed of an off-the-shelf application with the flexibility of a custom application. Open source communities with fellow enthusiasts helping and learning from each other are also a valuable resource for individuals interested in LLMs.

Building custom LLM applications tailored to your business needs is a strategic investment that offers many benefits from meeting unique requirements to enhancing efficiency, ensuring data security, and gaining a competitive edge. While off-the-shelf solutions have their place, businesses looking for a truly customized and scalable solution should definitely consider the long-term benefits of developing a custom LLM application.