3 KEY QUESTIONS WHEN PICKING AN ARTIFICIAL INTELLIGENCE PROVIDER

What should I look for in an AI provider? What’s the difference between ENAIA and other solutions on the market? Why do the prices differ so much between systems? How do I know that ENAIA is the best option for me? These are some of the questions raised by people who wish to implement Artificial Intelligence solutions in their business, but do not know where to begin.

The market is flooded with providers offering AI solutions, and their pricing and other features make the choice between them bewildering. So, here are 3 key points to look for when picking your Artificial Intelligence provider.

1. FORGET ABOUT SPECULATION, FOCUS ON A REALISTIC GOAL

The AI market often refers to specific performance and supervision figures with phrases such as “you’ll get 95% accuracy just by labelling 30 images.” However, when the solution is applied in production, these figures are usually a long way off the mark. This generates an expectation that is not met, which is very frustrating for users.

Remember this when picking your AI solution and instead of speculating with hypothetical performance figures, seek a platform, like ENAIA, that focuses on a realistic, tangible goal: achieving maximum performance as quickly as possible.

2. HONEST PRICES.

UNDERSTAND THE PRICING SYSTEM

Another factor that you should understand when picking a provider is how the pricing system works. The prices for the Machine Learning solutions that solve specific problem issues are not usually transparent. This is probably because it is very complicated to estimate the work that goes into training a specific AI system.

Consequently, you should look for a provider that is clear about their service pricing from the start. In the case of ENAIA, we seek maximum transparency and offer a standard price from the outset. Why? Because ENAIA aims to provide all the tools that the customer needs to teach the AI, although the amount of effort dedicated to improving will depend on the customer. This eliminates that uncertainty, so we can set a standard price with no tricks for our technology.

3. NOT EVERYTHING IN MACHINE LEARNING IS DEEP LEARNING

Most AI providers focus on vision tasks or natural language processing (NLP). Why? Because this type of task tends to be more generic and recurring in many use cases, making it simpler to build pre-trained models that do not require specific training. However, there are an infinite number of tasks that are not related to vision or NLP. In these cases, the range of solutions with competitive and transparent prices is narrow.

With ENAIA, we can provide in-depth knowledge of AI, offering technology that can automate tasks that, as well as vision and NLP, also address other types of applications such as:

  • Predictive maintenance that allows companies to look ahead and predict problems before they become a threat.
  • Predictions of time series that use data to predict values (past or future) thereby improving the company’s organisation.
  • Data mining that makes it possible to analyse the data in tables to extract relevant information from them for the company.