Comparing different types of AI/ML Partners
- Posted by GM, Digital Solutions
- On December 3, 2020
- AI, Data Science, Hiring, Software Development
Companies looking to take advantage of Machine Learning (ML) must overcome one significant challenge. Most organizations lack the ML expertise from AI partners needed to fully realize their goals and see a project through to completion.
Companies that lack machine learning expertise frequently seek out and benefit from partnering with a service provider specializing in AI projects and implementations. In a fiercely competitive talent market, these partnerships often become the lynchpin to closing a skills gap, so companies can advance their AI initiatives by completing a project, on-time, within budget and producing the outcomes stakeholders expect.
When choosing from AI partners, it’s critical to select one with the right skills and experience for your organization’s specific needs.
Examples of AI/Machine Learning Service Providers
Some ML providers specialize in business or compliance consulting, while others might focus on a specific technology platform or industry sector. Full stack ML and AI partners help companies with all stages of a project – from gathering requirements to production deployment. What follows is a more detailed look at the most common types of machine learning service partners, to ensure your organization makes the right choice.
General Consulting Firms
Some potential ML partners operate like a business consulting firm. They tend to promote experience in a variety of industry sectors, with several successful projects in AI-related technologies. Typically, these providers offer broad strategic recommendations, as opposed to detailed technical specifications or code. They make a valid option for companies that need direction on how to best leverage the possibilities of AI and ML. However, they can be costly and are generally only focused on the enterprise.
Specialized Machine Learning Developers
Other AI/ML providers specialize in a certain business vertical or technology area. For example, some specialize in industries that are highly regulated such as, healthcare, biotech, and financial or securities companies. Others may primarily focus on manufacturers, industrial firms, or even agriculture where AI can be applied to increase productivity or address process automation. Depending on the nature of your company’s business, a specialized AI/ML provider might be the right choice.
Specialization also happens within ML technologies or with one specific cloud vendor (i.e, AWS or Azure). One provider might focus on crafting detailed machine learning models, while another is known for strong data analysis and business intelligence work. It’s also possible that neither provider has much experience with software engineering, production deployments, or post-project support. When you engage this type of specialized provider, it’s important to understand your applications for ML first to assess their skill alignment with your needs.
Platform and Tools Companies
These machine learning partners offer specific, proprietary platforms to accelerate parts of the AI/ML processes. They can be smaller companies offering specific data platforms or cloud providers. Typically, they only provide the technology platform and rely on a partner network for implementation.
Similar to specialized ML developers, platform and tools companies are a good fit for companies that have a full understanding of your applications, a team with strong ML capabilities, and a specific machine learning problem to solve. The downside of working with these companies is the restricting orientation around their platform’s capabilities. This can lock you in, even if it’s not ideal for meeting your specific business objectives or developing the right long-term ML product roadmap.
End-to-end Machine Learning Services Partner
A fourth type of ML service provider is a full-stack organization, able to assist on an ML project from its inception until final deployment. In short, they are experts in the entire software development methodology, including analytics and machine learning model development. Companies that have an idea of their business objectives, but aren’t sure of how to use AI/ML to reach those objectives, may benefit from an end-to-end ML partner. By providing analytics, they can take companies from data analytics to insights that support intelligent business decisions.
Typically, they follow a platform-agnostic approach to their technical work – never tying themselves to a specific vendor or software stack. In the end, these providers make a great choice as a partner for businesses new to machine learning, as well as those facing skill-set limitations within their internal team.
Full-stack service providers also provide relevant business acumen within multiple verticals. While a provider that specializes in a specific vertical might be the right choice for a larger business with unique requirements in that same sector, they may lack the technical know-how possessed by a full-stack company.
Ultimately, the company must analyze its business needs in detail to determine which type of ML provider makes the best fit as a partner.
Strategies For Evaluating an AI Consulting Partner
Before evaluating potential ML consulting partners, it’s critical for a company to first look at its own skills and experience. Are there in-house resources experienced in machine learning projects, or are there constraints due to difficulties hiring experienced machine learning or data science engineers? Are they new to the technology? How much does the business vertical and expected outcomes influence the project requirements? These and other similar questions will help determine which ML provider type will be the right fit.
Companies that have not defined their goals or determined the potential benefits of machine learning, may prefer working with a business consultancy first. Some organizations have strong machine learning maturity and a well defined project scope, but simply lack a certain specialized expertise to complete their ML project. They may benefit from a more specialized partner.
Most companies will fall in the middle. They understand what they want to accomplish, but aren’t sure specifically how to use machine learning to realize their goals. Working with an end-to-end full-stack partner could help define the business problem and see the solution through to completion.
To assist companies with this important decision, Daitan crafted an e-book, How to Evaluate an AI Consulting Partner Using a Risk Assessment Decision Matrix. The book takes a thorough approach to help companies understand the advantages and risks of each ML provider type.
As a full-stack ML consulting partner, Daitan offers a unique set of skills and experience with artificial intelligence. Our platform-agnostic solutions ensure companies reap the benefits of AI without being tied to a specific vendor or technology stack. Connect with us to see how we can help your business succeed on its next machine learning initiative.