Compatio AI specializes in product configuration and recommendation solutions, combining technology with human expertise to help businesses and customers make better product decisions, increasing revenues and improving margins for brands and retailers throughout the customer journey. Pulse 2.0 interviewed Compatio AI founder and CEO Tim Baynes to learn more about the company.
Tim Baynes’ Background
What is Tim Baynes’ background? Baynes said:
“I was trained as a cognitive scientist with a focus on cognitive psychology and computer science. Early in my career, I worked on knowledge management and expert decision-making, collaborating with cognitive psychologists to study human expertise in high-risk domains like military operations and emergency response. In the mid-90s, I transitioned into information technology, where one of my initial projects involved building a product configurator for a Salesforce automation system in Ohio. This led me to KPMG, where I helped establish a product configurator practice and served as the lead technical architect for all related projects.”
“In the early 2000s, I joined Oracle where I became a Director in the consulting division, specializing in configurators. During this time, the industry saw a shift from standalone product configurators to integrated Configure, Price, Quote (CPQ) systems, which streamlined the process of configuring, pricing, and quoting customized products. Oracle further integrated CPQ into its entire order capture, sales, and fulfillment stack, handling every aspect of the configured product lifecycle.”
“After Oracle, I worked for a system integrator focused on configuration before joining Gartner as a Research Director, covering CPQ and related technologies. In 2018, I founded Compatio, leveraging my extensive experience in the field to address the evolving needs of businesses in this space.”
Formation Of Compatio
How did the idea for Compatio come together? Baynes shared:
“The concept of Compatio originated from challenges I encountered in the late 1990s while implementing a massive product configurator system for a manufacturer of cellular network equipment. This equipment needed to be integrated with other networking products, like routers and switches, to ensure compatibility and seamless operation. The complexity of quoting a combination of configurable products from different manufacturers posed a significant challenge, one that was common across various industries, from telecom to HVAC and medical devices. At the time, there was no efficient solution to address this problem.”
“The idea for Compatio solidified as I observed this issue not only in my professional work but also in my personal life as a cyclist. Building a new bike every couple of years, I faced similar compatibility challenges—selecting frames, wheels, and drivetrains from different brands and ensuring they worked together. This realization led to the development of Compatio, starting with a database of cycling components that could recommend compatible parts for e-commerce sites.”
“We launched Compatio by focusing on cycling, a simpler domain compared to sectors like HVAC or telecom, and used it as a stepping stone to build a robust platform capable of addressing the more complex challenges in B2B markets as the system evolved.”
Favorite Memory
What has been your favorite memory working for Compatio so far? Baynes reflected:
“My favorite memory was winning our biggest recommender deal to date and seeing it perform exceptionally well during the customer trial. It was incredibly validating to see years of work pay off, knowing the potential was there. That moment was a real thrill. While exciting things happen daily, much of it is now on the R&D front, so I can’t share specifics.”
Core Products
What are Compatio’s core products and features? Baynes explained:
“At Compatio, our two key products are Compatio Commend and Compatio Configure.”
“Compatio Commend is our recommendation engine. It combines precise data, human expertise, and predictive AI to create personalized, relevant recommendations for every user. It can handle multiple product combinations and relationships simultaneously, whether it’s optimizing recommendations across hundreds of thousands of SKUs or helping users construct complex, customized product solutions. The results are immediate and only get better as the platform continues to optimize.”
“Then there’s Compatio Configure, which guides users in building solutions that actually work in the real world. It uses what we call Real Intelligence—a blend of AI and human expertise—to calculate the best-fit compatible options. This tool is designed to handle complex build-to-order products or systems of components, applying intricate rules to make sure everything fits together perfectly. Plus, it integrates seamlessly into your existing system, handling large datasets with ease, and providing a smooth, responsive configuration experience.”
“Both of these tools are powered by our Product eXpert Engine, which quickly delivers hyper-accurate product configuration and recommendations. This not only boosts revenues and profits but also helps retain critical institutional knowledge as your team evolves, ensuring expertise is always available to any user or system in your organization.”
Challenges Faced
What challenges have Baynes and the team faced in building the company? Baynes acknowledged:
“The COVID era was particularly challenging for us. At the time, we were focused on consumer markets like sporting gear, cycling, and fishing. When the pandemic hit, everyone flocked outdoors, and while you might think that would have benefited us, it actually hurt our business. Inventory was quickly depleted as people bought up all the available gear, leaving nothing to sell. Our solution is designed to help companies sell more, but during that period, they didn’t need help selling—they needed more supply. As a result, it was a tough couple of years.”
“Despite these challenges, we continued to innovate and build out our platform. By late 2021 and early 2022, as people started returning to work, we shifted our focus to the more complex B2B verticals, like industrial automation and electrical systems, which had always been our long-term goal. By the time the consumer market began to recover, we had already transitioned to where we wanted to be—serving the more intricate needs of B2B segments. But those early pandemic years were definitely tough, as we struggled to close deals and grow revenue due to the sudden shift in market dynamics.”
Evolution Of Compatio’s Technology
How has Compatio’s technology evolved since launching? Baynes noted:
“The work we do at Compatio is complex, requiring precision across multiple areas. Early on, we recognized the need for a robust taxonomy management system to create precise categorization schemes that accurately cover all products in a given domain, like cycling or electrification. Most e-commerce categorization systems aren’t optimized for the advanced, intelligent functionalities we provide. They lack the precise control over product data that we need. To address this, we built our own categorization and category management system, alongside a rule engine to encode human expertise about how products go together. This formed the foundation for our initial recommender system.”
“Over time, we enhanced the recommender by integrating advanced data science and machine learning capabilities, allowing it to learn from sales data, order history, and clickstreams. This evolution made our system more AI-driven while still retaining the encoded human knowledge. Simultaneously, we developed a full-fledged configurator, which is challenging but crucial for getting product configuration right. What sets Compatio apart is our ability to maintain a single knowledge base that powers both recommendation and multiple types of configuration workflows at an e-commerce scale, something few others have achieved.”
“As we evolved, we introduced guided selling, which combines the strengths of recommendation technology and powerful configurator capabilities. This approach guides customers to the right products and solutions and then enables them to configure the system to their needs. We’re now adding pricing and quoting functionalities, completing our CPQ system.”
Significant Milestones
What have been some of Compatio’s most significant milestones? Baynes cited:
“Compatio was founded in 2018, funded in 2019, and secured our first customer in late 2019. Our initial product offering was a recommender, followed by a lightweight configurator called SmartBuilder in 2020. We then focused on developing Real Intelligence™ which gained significant traction in 2021 and 2022. This advancement allowed us to pursue much larger deals.”
“We transitioned from working with small specialty consumer products, like cycling and fly fishing, to more B2B and industrial segments as our platform has matured.”
Customer Success Stories
After asking about Baynes about customer success stories, he highlighted:
“For one large customer we were pursuing, their business case required a 30x return on investment.”
“To win the deal, they requested a proof of concept, comparing our recommender against their homegrown system and a major competitor from Silicon Valley, which was significantly larger and better funded than we were at the time. This competitor’s recommender was performing so poorly that they pulled the plug on it after just three weeks.”
“We were brought in, and from day one, our recommender outperformed both their internal system and the competitor. We started out running on 50% of their customer sessions in an A/B test. The test was supposed to run for 30 days, but halfway through, we were doing so well, our customer decided to expand our coverage to 100% of their traffic before the test was even over.”
“They achieved their 30x ROI target, validating our approach and securing us the deal, and they just renewed with us earlier this year.”
Funding
When asking Baynes about the company’s funding details, he revealed:
“I can’t go into too many specifics, but so far, we’ve raised over $7 million from our early investors. We’re also preparing to raise a Series A in 2025.”
Total Addressable Market
What total addressable market (TAM) size is Compatio pursuing? Baynes assessed:
“So, that’s actually hard to calculate. Our go-to-market strategy focuses on verticals with complex, large-scale industries, starting with industrial automation components and electrical systems—markets valued at over a trillion dollars globally.”
“Our revenue potential in the electrical sector alone is in the hundreds of millions. As we expand into other industries like building materials and other B2B products, our revenue potential could realistically reach a billion plus. But over the next three to five years, we foresee the potential to reach $100 million in annual recurring revenue (ARR).”
Differentiation From The Competition
What differentiates Compatio from its competition? Baynes affirmed:
“Compatio is the only recommender/configurator system in the world that’s optimized for dealer, distributor, contractor, and e-commerce use cases. While many configurators are built for manufacturers, much of the actual configuration work happens after the manufacturing stage, at the dealer, contractor, or integrator level. Here, products from multiple companies, some configurable and some off-the-shelf, need to be brought together at a digital scale. Compatio is unique in offering the capability to do this, and we can do it more cost effectively than any alternative.”
“Additionally, we combine recommendation and configuration into a powerful guided selling solution, something that sets us apart from the competition.”
Future Company Goals
What are some of Compatio’s future company goals? Baynes pointed out:
“In addition to expanding into other industries that I mentioned, we’re focused on making our products increasingly automated and continuously innovating to optimize knowledge and data acquisition, which will allow us to expand into new industries more quickly.”
“While we can deploy our solutions in a headless manner using APIs, which allows us to integrate with any digital sales, customer service, or marketing channel, we’re also building more out-of-the-box offerings for common platforms. Currently, we’re integrated with Shopify and Magento, and we’re adding BigCommerce and Optimizely for Q1 release.
“Finally, we’re excited to announce that we’re releasing a new product called Guide, in Q1. Guide is a dedicated Guided Selling application – it functions like an expert salesperson and guides the user through matching complex requirements to either off-the-shelf or configured products, or solutions made up of either off-the-shelf or configured product. Guide is a hybrid of both recommendation and configuration technology and distills everything we know into one app that unifies the customer experience to discover, select, configure and buy products in complex industries.”
Additional Thoughts
Any other topics you would like to discuss? Baynes concluded:
“The idea of a product expertise engine is becoming more critical, especially as industries face what many are calling a growing crisis in product expertise. A lot of companies that took off in the ‘80s and ‘90s are now seeing their key experts—many of them baby boomers—retiring. These folks have all the knowledge in their heads, and as they retire, that expertise is walking out the door. Replacing them isn’t easy, especially in today’s labor market. It takes years to train new experts, and finding the right people with the aptitude and background is a real challenge.”
“That’s where we come in. Our entire go-to-market strategy is built around addressing this exact problem. Some companies think AI alone can solve it, but the truth is, AI can’t handle everything. You can’t just rely on data science and machine learning to figure out product compatibility and configurability. These are complex product ecosystems with systems of components that are engineered to work together. AI is getting better fast, but it can’t get it perfectly right all the time, especially in a domain like this. You need a combination of human expertise plus machine learning to configure and recommend both accurately and optimally.”
“In industries like construction, getting product compatibility right is a matter of life and death. You can’t afford to guess, and AI alone sometimes does just that. That’s why our solution, which blends AI with real human expertise, is so essential. It’s all about ensuring accuracy and reliability where it matters most.”
