Salvaging your Failed AI Project
3 out of 4 AI projects are failing. We would know, because these days we're almost exclusively onboarding clients that's already failed with some other company. A couple of days ago we were contacted by a university. They had a list of ~500 courses and they wanted an AI chatbot allowing students to search for and discuss these courses with the AI. They had tried several different vendors, but the problems they're experiencing with all of our competitors is that questions such as these simply don't work.
- Tell me more about course 2134
- List all courses related to computer science
- What courses starts the 15th of August
The above problem originates from Vector Similarity Search (VSS) and how it finds relevant information. The fix is to combine traditional VSS search and RAG with "AI functions". Such AI functions can be seeded into the LLM, giving the LLM "exact search" capabilities, resulting in that queries such as the above will instead use "exact search" and not VSS. Almost none of our competitors can do this, and we're practically alone being able to deliver solutions to the above problem. In addition, there's a lot of companies having such problems, so it's kind of a really big deal. But really, the above is just an example of problems our customers have already faced and failed finding solutions to.
All AI Solutions Providers are Not Created as Equals
Most others will give you a URL and a username/password combination, and wish you good luck solving your problem. We're different, and by different I mean we'll work closely with you, until you've got a solution to your problem. Today almost 100% of our clients needs some sort of custom software development to solve problems such as illustrated above. This implies that we're the only ones who can solve their problems due to using Magic Cloud which allows us to easily develop such custom functionality.
In addition, problems such as the above, can also be solved by implementing reusable solutions that benefits all clients. This results in some "funny math", where we can work dozens of hours for one client, paying us no more than $298 per month, yet still financially justify it since it drives the product forward, and benefits all clients - Both existing clients and future clients.
This process is "by design" and a strategic decision we made before we even created a single line of code in our platform.
Projects not Products
We don't deliver "products". Our process is that each customer is an individual "project". To understand the difference, imagine hiring an architect to create a house for you, or buying an existing house. If you hire an architect, he will deliver something exactly matching your needs. If you buy an existing house you'll have to accept it as is.
Sometimes "products" are good enough for some use cases, but our experiences related to AI is that this is much less common than you think. The example I started out with for instance is currently being applied by some 25% of our customers, and it's theoretically impossible to solve it with a "product", because each individual search function would purely logically have to be different and search for different things.
The problem "compounds" because most customers don't even understand why they're experiencing such problems, so they cannot even construct a phrase that correctly describes it. This is because from their point of view "the AI simply doesn't provide the correct answers", while from our point of view it's a matter of how we extract RAG data, and whether or not we're choosing VSS search, exact search, or some combination of the above. The understanding of the solution, requires a deep understanding of the problem - In addition to an understanding of the business processes and workflows of the customer. And this is only possible with a vendor that spends a lot of time understanding your business, data, and problem - For then to deliver a solution. This is the reason why we're more espensive than others, because we spend more time understanding your business, and time is money!
If you want to discuss your AI project with us, we'd love to hear you out. If yes, you can schedule a meeting with us below. And of course, an introductory conversation is 100% free of charge and comes with no obligations to buy.
