You are ready for AI solutions when you have both the data and an internal team with the technical expertise needed to support AI models. You may have already experimented with a few tools—perhaps with unsatisfactory results. So, where do you go from here? Should you try a different tool? Should you partner with a solutions vendor? If you choose a vendor, how will you ensure they align with your internal team and contribute to your success?
There are many factors to consider when purchasing products or hiring a services firm to develop a custom solution for your organization. This guide will help you navigate that decision-making process. We’ll explore how your organization can determine which AI solution approach is best suited to your unique challenge.
There are two types of AI solutions: packaged and custom. Packaged tools are mass-produced, while custom solutions are designed to address a specific challenge, opportunity, or question—or sometimes all of the above.
AI is still relatively new in many industries, and numerous general packaged tools are available on the market. As former software professionals, we understand that when you're just “dipping your toes” into AI tools, it can be easier to opt for off-the-shelf solutions from trusted brands. Solution exploration is critical for business leaders, who often face the added pressure of delivering results. Despite their high cost, packaged tools are frequently chosen due to these pressures.
Packaged Tool Limitations
AI solutions involve much more than simply “plugging in” a software product and turning it on. Many packaged tools—even those marketed as the proverbial “silver bullet”—won’t resolve your unique challenges because they are not trained on your organization’s specific data or tailored to your particular use case. And this matters.
A generic software solution designed for broad use will produce generic results, regardless of how skilled your internal team may be. When a company "bends to the tool," it often sacrifices desirable features and settles for compromises that limit what can truly be achieved.
Your Internal Team’s Capabilities
Whether you choose a packaged tool or a customized solution, it's essential to assess your current team's capabilities. Do they have experience specifically in AI and in implementing and managing packaged software? Have they successfully worked with vendors to implement custom solutions before?
No matter how talented your team is, AI remains a relatively new field for most. The software is new, the data being collected is new, and success requires both AI expertise and a proven track record. We've seen many companies across various industries waste significant time and money by relying solely on internal teams to manage AI projects. In fact, many companies start with a packaged solution and, after struggling to customize it, end up hiring a vendor—resulting in costly, partially supported solutions.
A notable trend in 2021—accelerated by the COVID-19 pandemic—has been the shift to digital processes across industries. With increased digitization comes more data, and with more data, the opportunity to analyze it effectively. Many companies are building internal data science teams to drive AI and machine learning innovation, creating custom solutions to gain a competitive edge.
While this strategy can be effective, it is also expensive and challenging. Attracting, compensating, and retaining skilled data scientists—especially outside the tech industry—requires significant effort and investment.
Choosing a Vendor for a Customized Solution
If you don’t have the budget to build a multi-million-dollar internal data science department, partnering with experienced service providers is a more cost-effective option. Collaborating with these providers while leveraging your internal team’s expertise can help you build the solution you need without breaking the bank.
Moreover, if the solution involves critical aspects of your business or internal processes, this partnership ensures you meet all requirements without compromise. The service provider brings specialized expertise, while your internal team contributes valuable domain knowledge. As the vendor lays the foundation, your team gains real-world AI experience, empowering them to enhance and expand the solution in the future.
Educate Yourself on Open Source Libraries
Keep an eye out for vendors offering packaged solutions that are actually built using open-source (free) libraries or tools widely available online. These open-source resources are vast and continually evolving. The right vendor should transparently identify and leverage these tools to save you time and money. Transparency in this process is key.
Choose a Vendor with the Right of Expertise
Pick a vendor with expertise in the following areas:
Your industry: Knowledge of your sector's unique challenges.
Your role: Understanding the needs and objectives of your function.
Software Development and Integration: Proven technical skills in developing and integrating software.
Solution Building with Proven Results: A track record of success, demonstrated through case studies and testimonials.
Steer Clear of “Yes” Vendors
Beware of vendors who simply tell you what you want to hear. Instead, choose a partner who will be strategic, thoughtful, and willing to challenge your assumptions. Look for vendors who ask insightful questions about your data and business processes and collaborate with your team in a friendly, yet rigorous, manner. A true partner will help you strategize, plan, and build a solution that delivers meaningful and measurable results.
Pick the Right Internal Leader
Carefully consider who from your internal team will manage the vendor relationship and oversee project execution. Business leaders often assume their internal teams can handle the work more cheaply than hiring consultants, which can place significant stress on team leaders. They may feel they’re not "good enough" if external help is brought in.
To bolster morale, reinforce your confidence in your technical team’s abilities. Remind them that AI is a new field for everyone and emphasize that your goal is to ensure they have the support and resources needed to succeed. The right vendor will recognize these dynamics, fostering collaboration and maintaining focus on the ultimate goal: delivering a successful solution together.
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.
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.