Machine Learning Consulting: Everything You Need to Know

In business, there is always a demand for new and innovative ideas. Machine learning consultancy is one such service that can provide tremendous value to companies of all sizes. This type of consultancy has become increasingly popular in recent years as more and more businesses are looking to take advantage of machine learning techniques to improve their operations.

In this blog post, we will explore what machine learning consulting is, where and when it can be applied, and what ML consultants do in this field. We will also offer tips on selecting the best machine learning consulting company tailored to your needs, as well as how to work with them effectively once you make your selection.

What Is Machine Learning Consulting?

As with any technology, machine learning only contributes to the project’s success if applied thoughtfully. Regardless of your niche and the degree to which ML will interfere with your project, you will always need a solid plan preceded by an in-depth analysis.

Will you even need to engage in machine learning to achieve your goals? What challenges related to applying ML should you be conscious of? How can it contribute to your revenue? How to formulate relevant KPIs for the machine learning-based project? All these aspects are worth looking at before even deciding to employ artificial intelligence in your project or making a case for the company’s digital transformation. And that is where the machine learning consultant comes to the scene!

Putting it simply, the goal of machine learning consulting is to maximize your revenue related to implementing this technology while reducing risks related to it.

Machine Learning Consulting Services

Machine learning consulting is a service many software houses provide as a part of pre-project preparation. However, machine learning consultants can also intervene throughout already launched projects or work on reformulating those that did not deliver expected results.

Consultants help you evaluate the added value that ML can bring to the project and analyze the challenges and possibilities tied to its implementation. Later on, their role is to help the company pick the best methods, technologies, and project methodologies so that the project has maximum chances of success.

Use Case Evaluation and Advisory

Artificial intelligence is an umbrella term that involves various technologies connected with one common feature – they mimic the human way of thinking and acting. Machine learning is its sub-discipline that allows computers and software applications to gain insights and predict increasingly better outcomes with time. You can combine various techniques that fall under this category, depending on the specifics of your project or the product you are planning to deliver.

At this point, the machine learning consultant’s task is to help you to compose the right set and assess the project’s feasibility. By evaluating your use case, they can suggest the choices that your project will benefit from. For instance, if your project aims at streamlining customer service, it will likely involve natural language processing. If you want to provide a personalized shopping experience for the customers of your eCommerce store, look at recommendation engines. Monitoring manufacturing processes may require engaging a computer vision system composed of image-capturing devices and a classification model. Suppose it’s a specialized task, like, for instance, monitoring embryo development (our recent farming industry use case). In that case, the consultants will suggest a specialized solution, like AI-fuelled time-lapse imaging coupled with a predictive analytics model. These are just examples – there are thousands of configurations possible.

Depending on the type and complexity of the problem you are trying to solve, you may choose different kinds of algorithms. The consultants should be able to suggest the machine learning models that will contribute the most to solving them while engaging minimal resources. They will also advise on the data sets needed to proceed with the ML project. Should it be supervised, unsupervised, or semi-supervised? Should you choose linear regression, Naive Bayes, or Nearest Neighbor? They will help you determine whether your project will benefit from engaging in deep learning. Contrary to common conviction, more complex does not always equal better, but in some cases, they are necessary. Neural networks can become a project’s bottleneck if their use is not justified.

AI Strategic Consulting and Project Roadmapping

Planning is the core of any project, but in the case of those that engage artificial intelligence, getting the plan right is absolutely essential. Once you know which technologies you will employ and for what purpose, you should define a pathway that will lead you toward your goals. An experienced artificial intelligence consultant will guide you through this process, leaving you with a complete machine learning project roadmap that includes the milestones, resources, deliverables, and expected timeline, among others. With their expertise, you can adjust these parameters to the specifics of the artificial intelligence projects, which have very particular demands.

Having a roadmap ready, together with your AI consultant, you can evaluate the ROI of AI - will the project bring the benefits you’re seeking? The crucial question and answer will help you decide whether or not you should proceed with your idea.

Data Science Analysis and Data Quality Audit

If you want your machine learning model to deliver the expected results, you need to feed it with a lot of data. For it to constitute its logic, it needs to analyze the input and draw conclusions from it. The more data there is, the more accurate your results will be. That’s why the size of your dataset should be the first aspect the machine learning consultant analyzes. They may suggest appropriate data augmentation techniques to solve this issue if the quantity seems insufficient.

Quantity is one of many aspects you should consider when implementing machine learning solutions in your project. Quality matters even more. The consultant should be able to conduct a data quality audit to help you evaluate whether it matches the requirements of a chosen model and the outcomes you’re looking for. At the same time, you should receive advice on the preparation methods. Do you need a labeled or unlabelled dataset? Which quantity of data units will satisfy the model’s demand? After the consultation, you should have no more doubts.

Support in Building and Training In-House Data Science and AI Teams

Another aspect the machine learning consultant can help you with is handling your in-house resources regarding artificial intelligence expertise. Together, you can analyze whether the resources you have at your disposal are sufficient to handle the complexity of the AI solution.

If it turns out that you need additional support, the consultant can help you define the necessary tech stack and the model of outsourcing that could work the best for you (team extension/body leasing/external development team). If you prefer to do things on your own, the consulting team may also be capable of training your in-house specialists or providing support in the recruitment process.

When Should You Reach Out for a Machine Learning Consulting Company?

We recommend reaching out for machine learning consulting support whenever you consider introducing this technology in your project – even if you have already worked with artificial intelligence solutions. From our experience, a thorough consulting session always helps to see things from a different angle.

Being immersed in the project and excited about its potential, you may struggle to see the red flags or potential dangers, even if you are an expert in your domain. A fresh look with which the consulting team will analyze your project can bring in additional value.

How Does Machine Learning Consultancy Work?

Machine learning consultancy may adopt different forms depending on the spectrum of technologies you are going to apply and the stage at which you are reaching out for support. The team can join you at any moment – it does not necessarily have to assist you from the beginning of the project. However, in order to proceed with the process, they will need you to provide them with technical documentation, project roadmap and backlog, the databases you have at your disposal, and all the other material that may be relevant.

The machine learning consulting team can assist you throughout all the phases of the project or during a particular one when you need additional help. What is an outcome of a consultancy service? That depends on what you need and what you agree on. It can be an audit or a report that contains all the conclusions and recommendations.

How to Select the Best Machine Learning Consulting Company?

Since we are already discussing how machine learning consulting services work, we will also touch on the question of choosing the right partner. We recommend adopting similar criteria as in the case of picking an outsourcing software development company. In the end, consulting and software development often come in the package. However, the recommended criteria may change slightly due to the nature of this service – in the end, advisory and practical implementation require different competencies. Here’s what we suggest keeping in mind.

Portfolio of Successful ML Projects

The number one criterion is the portfolio. It reveals the strong and weak sides of your potential consulting partner. Look for AI-oriented case studies. We wouldn’t say that a limited portfolio disqualifies an ML consulting company. Quality over quantity – if they have a few positions in their portfolio but well-documented, with all the details included, thoroughly described implementation process and results, it is likely worth giving it a go. Analogically, if the portfolio is rich but lacks details, we would treat it as a red flag.

Wide Team of Machine Learning Experts

They say it takes a village to raise a child. And it takes a whole bunch of specialists to develop a machine-learning solution! Aside from machine learning engineers who will design and deploy your machine learning model, you will also need to engage data scientists who will gather sufficient data and select a dataset that will serve as an input, processing and labeling it afterward. MLOps specialists will take care of the efficient implementation and maintenance of the machine learning solutions. Also, the product managers and designers you engage should have expertise in ML projects.

End-To-End Offering

This criterion will be relevant for you if your in-house resources are limited or if you don’t have software development professionals at your disposal. In this case, an end-to-end machine learning service that covers consulting and further development, implementation, and maintenance will likely be the most favorable option in terms of time and finances. The “full package” always ends up being the most cost-effective. Plus, it makes it easier to maintain consistency. The consulting team has to gain a deep understanding of your project to provide advice. So, if they later take care of your AI product development, they can easily apply that knowledge in practice.

Industry Understanding

Even though every project is different, the use cases within one industry are often quite similar. The consultants who have already worked with customers from your niche know its specifics and pains. That makes it easier for them to find the right solutions and adjust technologies that meet your needs. As a result, it takes less time and less engagement from your side for them to deliver satisfactory results. How do you evaluate their industry expertise? Based on our own example – we prove it with our case studies and blog publications that contain extensively described industry use cases.

Agile Approach

The agile approach brings value to software development, but it is also worth sticking to it in the consulting phase. By dividing the work into short iterations, the consulting team can deliver insights much faster while you maintain the highest control over the whole process. You receive results in smaller batches, being able to implement them while the consultants are working on the following aspects of your machine learning solution.

The agile approach also means starting small with your project and investments. In our case, for some companies, we recommend organizing AI Design Sprint workshops that help our clients evaluate their ideas and the feasibility of AI opportunities within just two days of hands-on work.

The agile AI product management approach provides you with much more flexibility – when you want to change something in your cooperation or consult the results, you act right away.

Tips for Working With a Machine Learning Consultant Successfully

Keeping your expectations high is natural and recommended, but in order to achieve satisfactory results, the consultant will also need some effort from your side. The more collaborative you are, the better for the project. Here are some aspects we find essential based on the consulting experiences we have had so far.

Be Transparent About Your Needs, Requirements, and Hesitations

You will only benefit from it in the long run. It is not a competition or a tender, meaning you don’t have to show your project in the best light. Quite contrarily – we need to know its weak points to suggest the most relevant solutions. Remember – we, as consultants, are here to solve your problems. The more we know about your project, the better. Honesty is a crucial pillar of partnership, and it makes it possible for the consulting team to tackle the actual issues. Such transparency makes it easier for both sides to achieve the expected results.

You’re Here to Learn – Reserve Time for Your Team for Knowledge Transfer From ML Consultants

The consulting team is here to share with you – take advantage of that! They are not only supposed to guide you through the process of developing a machine learning solution but also enable your team to actively take part in this process (even if you’re passing all the development processes to the hands of an external team, your managers will benefit from learning). You can expect them to organize training sessions and Q&As that will provide your team members with the knowledge they need.

Embrace Experimentation and Graceful Failure

You are implementing technologies that are developing dynamically. There are still many unknown trails to blaze. Who knows – maybe you end up as one of the pioneers of machine learning adoption in your industry. We have already worked with such! In that case, there are often no use cases to follow and examples to learn with. That’s why you should be prepared for experimenting – and the possibility that it does not go as expected. However, you can reduce the probability of failure by engaging experts with expertise in your industry.

Define Expectations and Success Metrics Early

Success metrics show your team a clear direction and help to kick off the project with a solid dose of energy and enthusiasm. With a set of clearly defined, relevant KPIs, it is easier to establish a common vision that resonates with all the team members. At the same time, by having the metrics early, you will be able to detect issues that could escalate in the later stages of project development.

Benefits of Hiring a Machine Learning Consulting Firm

Machine learning consulting is a service that can save you a lot of worries. Whether you have any previous experience with artificial intelligence or you are a complete rookie, such support will allow you to rest easy. There are more perks that come with it!

Budget and Time Saver

Even though you have to invest in a pricy consulting service, this investment pays itself with more time. Thoughtfully planned and evaluated in terms of risks, your machine learning project will generate way fewer expenses in the long run. Plus, instead of gradually gaining expertise (often with some failures on the way), you can kick off the project with all the insights at hand, which will likely make you fulfill your goals faster.

Strategic Approach and Bullet-Proof ML Software Development Process

The consultants will help you prepare a project roadmap, establish relevant KPIs for the machine learning-based software development process and pick solutions that go in line with your needs. But they will also support you further in development, helping to solve dilemmas and issues ML developers often struggle with. They know them inside and out. Machine learning approaches problem-solving differently than traditional programming, which the teams are often used to. Consultants help them understand these differences and put this knowledge into practice, which results in fewer errors and problems in development.

Expertise in Creating Various Solutions

Consultants have worked on numerous projects, and they know that there are no universal solutions. However, having that experience, they can support you in dreaming big and selecting the most favorable options for your project.

Do you have a vision or idea you would like to discuss? We can help you understand how machine learning can contribute to it! Get in touch with us for more information.