As president of the Vonage Business division eight years ago, Clark Peterson felt secure that the company had a patent portfolio—a shield, so to speak, against those inclined to steal the technology. Beyond that, he didn’t think much about these documents. “I didn’t know there were ways to monetize the patents,” he told IFI CLAIMS. “I only knew that they were a comfort blanket.”
Peterson’s thinking changed after leaving the company and connecting with a Vonage customer, a patent legal firm that operates around the world. A few of the attorneys, who were also software developers, had developed proprietary software that imitated what patent lawyers do: portfolio analysis. Specifically, the process of evaluating what to hold, what to fold, what to sell or license, and what infringements might be lurking.
Patent insider
Who: Clark Peterson
Innovation cred: CEO of Ontologics, Communications pioneer
Favorite invention: An Ontologics homegrown invention: US Patent No. 11,494,419, filed in 2020 and granted in 2022. The patent protects a method for organizing large collections of technical documents by clustering similar groups of information. How? “It uses advanced models that analyze both the hierarchical taxonomy associated with the documents and the actual text within the documents to determine how closely related the documents are,” says Peterson. Ontologics, naturally, has a perfect use for this patent—structuring the patent data on its own platform.
“These lawyers took their secret patent analysis sauce and duplicated it into algorithms,” Peterson says.
That secret sauce is the genesis of Ontologics, a patent company that helps businesses and outside investors find the financial opportunities hidden in the bonanza of data just sitting there in the patents, waiting to be properly exploited. IFI spoke with Peterson, who is CEO of the company, to discuss the ingredients of that secret sauce, the reason why forward citations aren’t the be-all and end-all for patent value, how the company is incorporating AI into its platform, and why Ontologics chose IFI CLAIMS’ data to power its patent analysis. The interview has been edited for clarity and length:
IFI CLAIMS: Tell us about your background and how it led you into the patent space.
Peterson: I’ve been in the technology industry for 33 years. When I graduated from college, the cellular industry was new. I had started a window tinting business in college to fund my education. I was on the go, and I needed a cell phone to operate, so I owned one of the early ones—a portable bag phone that you’d carry over your shoulder. So when the cellular companies came out to conduct interviews at my college, I signed up. I brought my cell phone bag to the meeting because I had been working; during the interview, I was told that I was the first person the company had interviewed who had actually used one of these cell phones already. They immediately hired me to be a sales rep for Cellular One.
I moved up pretty quickly in the corporation. Cellular One was sold to AT&T, and it became AT&T Wireless. In fact, AT&T Wireless didn’t exist until they acquired Cellular One. After that, I was involved in one communication company after another. We started Nextel and took that public and then sold it to Sprint. Then came NextLink, later named XO Communications which also went public. Then we started a company called Clearwire. I was the first employee. Clearwire went public in 2007 and was sold to Sprint in 2013. Those assets all belong to T-Mobile now. They now have and utilize all of the Clearwire 2.5–2.7 GHz spectrum. Then I started a company named Telesphere. I sold that to Vonage in 2015. In the wake of that sale, I became president of Vonage Business, which was later sold to Ericsson.
These were all high-tech companies, so patents were key to protecting that leading edge technology. While president of Vonage, we had a customer that was a global patent law firm in Arizona. After I left Vonage, they asked me to look at a software platform they had been using as a patent firm that they thought gave them an edge over other patent firms. The firm happened to have four patent lawyers who were also software developers. And the lawyers weren’t happy with the other options out there for patent analytics because they were all just search engines that would value patents on just one metric: forward citations. Leaders in the patent space were merely judged by which companies had the highest patent count. These lawyer/software developers wanted true analytics. Not just counts. They wanted something that could essentially mimic what they as patent lawyers do.
If you hire a patent attorney, you generally pay $30,000 for a review of the patent portfolio. The attorney can suggest which ones to keep, which ones to get rid of, which are most valuable, which ones should be licensed, which ones might bring money in a sale, and what companies might be infringing on the patents. That is patent analysis. These lawyers had created an algorithm for what they would do as a patent lawyer when they were retained. They took their secret patent analysis sauce and duplicated it into an algorithm. It’s really unique.
IFI CLAIMS: And that became Ontologics?
Peterson: Yes. When I looked at their software, I thought it was great stuff. I suggested sticking it in the cloud, creating a portal so that anyone can use it, and charging per seat. Basically creating a SaaS model that can still be used at the patent law firm but that could also be sold as a product for others to use. It’s what American Airlines did back in the day with its Sabre reservation system. They spun it off as a reservation system that almost every airline ended up using. So it’s kind of a similar beginning for us.
Our private equity and venture capital clients love our affinity score because they can figure out which companies complement each other. If they’re looking, for instance, to do an acquisition or do a roll up in the cloud communications space, they can easily find ten companies to consider.
IFI CLAIMS: How were you analyzing patents when you were in the telecommunications space?
Peterson: It was always so hard to analyze your patents before these Ontologics tools came out. As president of Vonage, we probably had 400 patents, I think. I felt good that we had patents. It was protection. But I didn’t know how to compare our patents to RingCentral. I didn’t know there were ways to monetize the patents. I didn’t know I could use the patents to find other companies that look like ours that we might want to acquire or how to otherwise use the patents for strategic decisions. I only knew that they were a comfort blanket, that having patents were a way of protection from those looking to steal the technology.
IFI CLAIMS: Give us more detail about what Ontolgics does. What goes into the secret sauce, as you put it, of this algorithm?
Peterson: When we look at patent strength, which is really the legal strength of a patent, there are 11 different factors in our set of algorithms. Most people look at just one thing to analyze patent strength: forward citations. We think differently about forward citations. If you’re getting cited a lot, you’re in a more crowded space for that patent, and so you have a lot of competition and less differentiation. So maybe the patent isn’t as unique or innovative. Or maybe the forward citations show it’s past the innovation curve and not as emerging. We use forward citations, but we look a lot at claim breadth and first claim and nine other factors to calculate innovation levels. Our algorithms create an emergence curve. To analyze the strength of a patent, our platform looks at all the CPC codes associated with it, and then mines the worldwide IFI CLAIMS universe of patents for others with similar CPC codes. Then it creates a market universe of companies that have similar technologies. These companies could be direct competitors or existing partners or seemingly unrelated, but they look like you because they have similar CPC codes. We then rank every one of those companies so the customer can see how its technology stacks up versus the other emerging technologies. We look at how close these emerging technologies are to each other. Customers using our platform can assess how leading edge or aged their technology is compared to others appearing on the scene right now. That’s the innovation score.
We do the same for all 11 factors, including, for instance, strength or assertibility, which comprises the legal score. We look at the geography. Patents filed in the U.S. receive a higher ranking for assertibility than others because if you can assert in the U.S., it’s worth a lot more than if you can assert in Malaysia where there is not that much competition as far as patent strength goes. So all these factors we’ve set up in our algorithms give strength scores, innovation scores, dominance scores, etc. Our private equity and venture capital clients love our affinity score because they can figure out which companies complement each other. If they’re looking, for instance, to do an acquisition or do a roll up in the cloud communications space, they can easily find ten companies to consider. If they want to license some patents or see who is infringing on one of their portfolio company’s patents, or understand their least valuable patents for grooming and cost saving, they can ascertain that with our tools.
A custom thing we can do is show customers possibilities for monetizing their patent portfolios. Who is my top partner? Who is my top licensee candidate? Who is my top potential acquirer? Ontologics provides real-world actions you can take to make money from your patents versus trying to figure it out on your own.
That’s why our products resonate with tech companies and financial professionals. Most of our competitors focus on serving patent lawyers and helping them find what they need for their own analytics. We try to make patent analytics accessible for those in these other industries.
IFI CLAIMS: How is AI changing the way you do business?
Peterson: We had already been using machine learning to do all our analytics in the past. Now we are using more and more AI. We’re also switching to an AI front end in order to make navigation of our platform easier. Our clients will soon be able to ask any question on the AI front end user interface, and it will query our proprietary information and give all those reports from our data and analytics. But if we don’t have the proprietary information to answer the query, they can get basic AI information. Anyone can do an AI front end, but one that can merge proprietary information with the basic AI out there is very powerful.
IFI CLAIMS: What else is important to understand about Ontologics?
Peterson: I think the main thing is that we’re not giving you a tool to search information and connect dots yourself. We connect the dots for you—in minutes, not weeks. And then you have the chance to decide whether you want to add your own secret sauce to it.
Ontologics provides real-world actions you can take to make money from your patents versus trying to figure it out on your own.
IFI CLAIMS: What general trends have you seen in the patent industry over the past few years and what do you think things will look like in the next few years?
Peterson: AI will change things dramatically. There will be more sophisticated analytics certainly. Everybody has to look at AI as a friend and a foe because there are ways it can replace you, and there are ways it can empower you. So AI will be the biggest trend that will be disrupting the industry, but also enabling the industry to reach new heights.
Other trends I see: how industries are going to use their patents to give them strategic information (as I was alluding to before) versus all this information simply being evaluated by patent lawyers for their clients. Now we’re going to see different industries and professionals assessing patents: private equity, tech execs. They’ll discover that patents are a wealth of knowledge that can be used for decision-making because they can see what competitors are doing and how they compare with the industry’s emerging technologies. Companies have always taken their most valued technology and put a patent around it. But patents are also a broad intelligence base that can be accessed by non-legal professionals to plan strategies.
IFI CLAIMS: Why did you decide to use IFI’s data to power the patent portion of your platform?
Peterson: We looked at the industry and talked to people in the field. I said before that we had patent lawyers who built the software. Those attorneys saw IFI as the most credible source of information. IFI’s patent data is broad, with information from China and many other countries. They have it categorized and put into a form that you can really use well for analytics. IFI did the important work of gathering global patent information and getting it into a good format.
