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Exploring Solutions & Finding the Right Vendor to Solve Your Problem

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Understanding your organization’s unique needs and tips to make the right decision


You’re ready for AI and you have the data and internal team with the technical chops you need to support the creation of valuable AI models. You may have even tried a few tools on your own already – and perhaps you had lackluster results. Where do you go now? Do you find a different tool? Do you find a solutions vendor to partner with? If you do pick a vendor, how will you ensure they jive with your internal team and help achieve success?  

There are many variables to consider when purchasing products or hiring a services firm to build something custom for your organization. This piece will help you navigate through this decision. We will cover how your organization can decide which AI solution approach is best for your unique challenge.


Packaged Versus Building a Custom Solution with a Vendor

There are two types of AI solutions: packaged and custom. Packaged tools are mass-produced, while custom solutions are tailor-made to suit a specific challenge, opportunity, question – or all of the above. 

AI is relatively new in many industries, and there are many general packaged tools available in the market. As former software professionals, we understand that when you’re “dipping your toes” into AI, sometimes it’s just easier to purchase something off-the-shelf from trusted brand names. Solution exploration is critical for business leaders and comes with the associated pressures of having to deliver. Even though packaged tools can be expensive, company leaders are often pressured to purchase them. 

Packaged Tool Limitations

As you know, there’s a lot more to AI solutions than just “plugging in” an AI software product and turning it on. Many packaged tools – even if their marketing says it will be the proverbial “silver bullet” – won’t solve your unique problem because they are not trained on the specific data in your organization, or for your specific use-case. This matters. 

A generic software solution that has been designed for the masses will yield generic results, no matter how talented the internal team is that is in charge of implementing it. This is because when a company “bends to the tool” the company forgoes certain “like to haves” and compromises on what can be achieved.

Your Internal Team’s Capabilities

Whether you pick a packaged tool or customized solution, it is important to review your current team’s capabilities. Do they have experience in AI specifically and in implementing and operating packaged software? Have they worked successfully with a vendor before in implementing customized solutions? 

No matter how bright and talented your internal team is, AI is a relatively new field to everyone – the software is new, the data being collected is new, and it requires experience in AI – as well as a proven track record of success. We have seen many companies – in a broad range of industries – waste a lot of time and money letting internal teams handle these projects on their own. In fact, we see many many companies want to start with a packaged solution – and by the time they go about hiring a vendor, they have already attempted to customize on top of the packaged solution. This can lead to very expensive solutions that are quasi-supported by software companies.

One trend we have seen in 2021 – and especially in response to the COVID-19 pandemic – is a shift to digital processes in all industries. With more digitization, comes more data, and with more data, comes the ability to analyze this data. Many companies are actually building up their own internal data scientist teams to accelerate their AI and machine learning innovation. This allows them to build their own customized solutions and drive competitive advantage. 

Depending on the seniority and experience of the team, this can be a successful strategy to pursue – albeit quite expensive and difficult.  Attracting, compensating, and continuously engaging data scientists without attrition is very challenging outside the technology industry.

Choosing a Vendor for a Customized Solution

If you do not have the budget to build out a multi-million dollar internal data scientist department, working with experienced service providers to build the solution you need – whilst working in tandem with your internal team – is much more affordable. Furthermore, if the solution you are looking for is related to critical elements of your business or internal processes, this partnership combining service provider expertise and internal team knowledge will enable you to build and deliver the solution that your organization actually needs, without compromising on any requirements. While the vendor lays the foundation, your internal team will acquire real-world AI experience which will allow them to build upon the solution in the future.


Tips for Choosing a Vendor

Educate Yourself on Open Source Libraries

Be on the lookout for vendors offering packaged solutions that are actually built off open-source (free) libraries or tools available online. These open source libraries are massive and growing daily. The right vendor will be able to identify these for you to save you time and money and this should be fully transparent. 

Pick a Vendor with the Right Combination of Expertise

Pick a vendor with expertise in the following areas: 1) Your industry; 2) Your role; 3) Software development and integration; and 3) Solution building with proven results. Read their case studies and testimonials.

Steer Clear of “Yes” Vendors

Ensure the vendor is not just telling you what you want to hear. Make sure they will be strategic and thorough thought-partners on this journey. Make sure they challenge you and your team on your data and assumptions about your business, ask probing questions, and will work together in a friendly, collaborative partnership with your team to strategize, plan, and build an impactful solution that yields a successful result.

Pick the Right Internal Leader

Be thoughtful in your decision on who from your internal team will lead the vendor relationship and project management. Frequently business leaders tend to assume that their internal teams can “get the job done” for much cheaper than a consultant – and this stress can weigh heavily on internal team leaders as they can feel like they are not “good enough” to get the job done and that their company had to hire externally. 

Reinforce your confidence in your technical team’s abilities to bolster their morale, and assure them that AI is a new science – it’s new for everybody – and that you want to make sure they have all the resources they need to get it right. The right vendor will be able to navigate these sensitivities as well to foster collaboration and keep everyone’s eye on the prize: delivering a great result, together.


Your Next Steps

The bottom line is: you want a solution that will not only add immediate value to your organization but also be flexible enough to grow with you. You do not want a stopgap measure – or else you’ll find yourself back at the drawing board in short order. We cannot stress enough how important it is to pick a vendor who is a true strategic thought partner and will help you build a solution that will help you long-term, and provide guidance and education to your internal team so they can manage the project moving forward.  


How Synaptiq Can Help

Synaptiq focuses on the humankind of AI; building a better world as we lean into an age of human and machine interaction. We believe solving serious challenges, making real impact and saving lives is worth every waking moment. So we collaborate and make thoughtful considerations across disciplines examining past, present and future models of merit. Whether history, science, math, nature, human behavior; they all inform the data and ideas that help us find answers to world-class riddles.

We keep our AI on people because AI is how we do it, humanity is why we do it.

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