How to choose an AI or data science consulting company?

This post is about how to select an AI, data science or machine learning vendor if you are planning to implement it in your organization.

Let’s see what AI, data science, machine learning and deep learning means.

AI or artificial intelligence comprises of machine learning and deep learning. Deep learning is special form of machine learning and uses neural networks. The below diagram from KDnuggets explains this well.

 

Every trade show you go or every vendor presentation you listen to, there is one thing you will find common which is some amount of machine learning or AI in the product or the company.

As if overnight, every vendor added AI or machine learning in their products. As if by adding AI or machine learning, all of a sudden their product has become this shiny new thing you want to get a hold of.

There is so much hype and confusion and it is important to select the right partner or vendor in your AI journey.

Things to look for when selecting an AI consulting services firm:

  1. Start with your use case: Always start with your problem. What are you trying to solve? More sales, less churn, better customer segmentation, better ROI in your marketing efforts, etc. There are two ways to look at this. Start tactically and select a problem to solve. Or think strategically and build an AI or data science team.
  2. Look at what a vendor did prior to data science or AI offerings: Did a vendor overnight started AI offerings or it is a pure play vendor. Every vendor can say they offer AI services but it is important to look at since how long they have been offering these services.
  3. Vendor capabilities: AI is a huge field. Is the vendor good in traditional machine learning or deep learning or NLP? Your use case dictates specifically what to look for in vendor capabilities. If you are looking to build a chat bot for your customer service or for your internal 1st or 2nd level support, look for a vendor good in NLP. If you are looking to do customer segmentation, look for a vendor good in traditional machine learning. If you are looking to do image analysis to detect cancer, look for a vendor good in deep learning.
  4. Vendor management team: Look for a vendor whose management has relevant experience in this field. Lot of companies claim they are a data science company but they may have started as a big data firm and started offering AI services.
  5. Vendor vision: It is very important to understand the vision and mission of an AI or data science vendor. A vendor without clear vision or mission or a grandiose mission is someone to stay away from.
  6. Customer service: This is pretty standard. A vendor without great customer service and great technology talent is not very useful.
  7. References: Again a standard requirement. At least get two references from their current or past customers.

We at WildFire provide data science, AI and big data consulting services. We are proud of our quality and on time delivery of AI, deep learning, traditional machine learning and big data projects.

If you are looking to introduce AI or data science in your organization, talk to us on how we can help.