Are you considering using an in-house team of Data Scientists to implement an Automation program? Before you make your decision, consider the following criteria.
Over the last 9 years, the team here at NLP Logix has developed hundreds of AI/ML solutions throughout a wide variety of industries. From building predictive maintenance models for the F-35 to detecting breast cancer tumors in pathology slides, we have seen a lot when it comes to AI and automation.
Often times we have clients who are debating whether or not to hire an outside firm such as NLP Logix, or build these solutions in-house by hiring an internal data science team. The answer to that question depends on several factors, so there is no right or wrong, but we wanted to highlight a few of the top reasons that firms have decided to work with us rather than going at it alone.
Think of that one skill that you are really good at, and then try to remember how good you were the first time you did it. Maybe it was the first time you swung a golf club, or when you first learned the piano. Our guess is that you probably didn’t break any course records when you hit the links or sounded like Mozart after a week of piano lessons.
The same philosophy applies to AI projects. The first ones are tough. You simply don’t know what you don’t know. Every AI project has potential pitfalls; issues with the data, trouble integrating the models into your workflow, stakeholders with different priorities and timelines. We know about these kinds of pitfalls because we’ve encountered almost all of them.
When you partner with our team at NLP Logix, we leverage our experience to not only identify these potential pitfalls, but also how to avoid them to ensure your project is successful.
When we talk to clients who have decided to build AI/ML solutions in-house, many believe they can simply hire one “data scientist” to deliver these projects internally. Here at NLP Logix we have a saying, “Data Science is a Team Sport”, which means that no one single person is an expert at all the skills needed to make an AI project successful. It takes a team of people who are experts at Mathematics, Statistics, ML Engineering and Software development to come together to build a successful solution.
Since we have a strong team with these skill sets, we are able to assign the right individuals, to the right phase of the project at the right time. As issues come up, whether it’s gathering and modeling the data, feature engineering, or getting the model into production, we have experts on the team who can solve these specific issues and keep your project on track.
Over the years, we have developed our own proprietary tools to help build a variety of AI/ML projects. These tools, known as LogixStudio, are built on proprietary algorithms and tools that enable rapid development and used for rapid integration into most environments. LogixStudio bindings allow different programming language to talk to each other so you do not have to invest in additional software or technology in order to apply a Machine Learning model to your operations.
This might not seem like an obvious reason to hire an outside firm for your AI/ML projects, but in the long run, most clients find we are more cost effective than trying to build these solutions in-house. One of the biggest reasons is the fact that we can complete projects 2-3 times faster than an internal team could complete them. When you factor in the cost of salaries for an internal team and also take into account the prolonged timeline, we are almost always less expensive.
In addition, we can create a long-term AI/ML roadmap and help advise on where the model can be hosted (cloud or on-premise) so you are not spending additional dollars to keep the model supported.
Whether you have already completed a few AI/ML projects and are short on bandwidth, or just started exploring how to apply AI and automation to your workflows, the team at NLP Logix is ready to help.
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