Last Sunday, I delved into the often misconceived notion of a seemingly easy recipe for a Retrieval Augmented Generation (RAG) solution. Many seem to believe it’s as straightforward as combining a vector database, a sprinkle of LangChain, and a dash of OpenAI. But the reality is far more intricate. Today, we shall investigate a more effective approach that goes beyond these oversimplified ideas.
To illustrate this, let’s revisit the example I mentioned about the bank. This takes us back to the turn of the century when a renowned bank enthusiastically jumped on the Internet bandwagon and started building their own Content Management System, imagining it would be a transformative asset.
However, it soon dawned on them that multi-language content rendering isn’t really a unique selling proposition (USP) of their bank, nor actually of any bank. In the dynamic world of banking and finance, being able to render content in multiple languages is undoubtedly valuable, but it’s hardly a standout feature. And with its own intricacies it isn’t easy either. A multi-million investment, they stopped the ill-fated venture a couple of years later.
What’s the Alternative?
Instead of fixating on what every other organization might be doing or adopting, the mantra should be to channel energy into one’s unique strengths. The answer lies in a two-pronged strategy:
- Leverage External Expertise: Partner with external professionals and vendors who specialize in the core platform. This should be their domain of expertise. Instead of reinventing the wheel, it makes business sense to let the these folks handle what they’re best at – they are hopefully doing it for a long time. Not sure if they are experts? Organizations like Gartner and Forrester are a good starting point. With respect to the RAG dichotomy I suggest to consult e.g. the Gartner Magic Quadrant for Insights Engines. The vendors mentioned know what information retrieval is – better than most upstarts. We’ve been at this for a long time*.
- Hone in on Internal Specialties: Focus internal resources on what isn’t easily available in the market. For our aforementioned bank, this meant developing a cutting-edge portal that provided users with a 15-minute delayed feed of stock market prices and quotes. This might seem commonplace now, but at the time, around 2000, it was groundbreaking. Here’s the kicker: This was a service no content management vendor offered. Yet, the bank possessed the necessary expertise. They understood the user requirements for such a service, had access to the crucial data, and went beyond to make this vision a reality. Notably, this portal still stands today, testament to its utility and the bank’s foresight.
Modern-Day Application
Drawing a parallel to the present day, the principle remains unaltered. Businesses should consider the offerings of platform vendors* and should focus their actual efforts on what sets them apart. A modern-day setup could for instance be:
- Imagine a company selling transportation tickets. Many customer requests for a simple ticket from A to B are already handled well. Their online purchasing process is reasonably straight forward and easy. But here and there a customer needs a more detailed answer or simply wants a trip recommendation. Obvious that a GPT based solution might come in handy.
- Let a vendor like us handle the platform / GPT side of things. Ingestion of data, handling of the full data life cycle process, user authentication and authorization, the actual user interface, and more.
- The company should focus its efforts to “GPT enable” the ticket vending process. This is not something any vendor will provide. For starters because none has access to said system.
- The result: Users can interact with the chatbot to quickly find events, compare ticket prices, and get recommendations. It can answer complex queries, handle multiple event searches, and even assist in transaction processes. This not only improves user experience but also streamlines ticket purchases. Additionally, utilizing the AI’s capabilities, it can predict user preferences based on past interactions, ensuring personalized event suggestions, making ticket buying more intuitive and user-centric. And yes, the same recipe may be applied to any business.
Concluding Thoughts
The lure of the latest technological innovations is strong, and it’s easy to get swept away by the tide. Yet, while integrating solutions like RAG can be valuable, it’s imperative for businesses to recognize what truly sets them apart. Sometimes, the real differentiator might not be a flashy new AI tool but a service or solution that caters to the unique needs of their clientele.
In essence, while the world rushes towards adopting every new technological innovation, it might be more prudent to take a step back, evaluate what truly matters, and invest in those areas. After all, in the vast sea of technology, it’s the unique solutions that stand out and stand the test of time.
* It’s vital to recognize that it’s more intricate than simply merging some Azure Services with Microsoft-provisioned OpenAI access A glaring challenge that comes to mind is the aspect of data integration and re-integration into the existing enterprise landscape. Why this is important? No company runs exclusively on Microsoft products. Thus, relying solely on their offerings can be limiting, especially when data integration extends beyond their product range.
** We’ve been in this business for very long. Gartner thinks of us as the Visionary in the space. Not convinced about the build or buy case? Here’s a paper. And our SquirroGPT solution brings the points made above to life. Try it for yourself.
*** Wondering which bank it is? Ping me. 😉
