Identifying Investment Opportunity on the Edge

May 20, 2021

This article is part of the Crunchbase Community Contributor Series. The author is an expert in their field and a Crunchbase user. We are honored to feature and promote their contribution on the Crunchbase blog.

Please note that the author is not employed by Crunchbase and the opinions expressed in this article do not necessarily reflect official views or opinions of Crunchbase, Inc. 


In chaotic and unpredictable times like these, when a band of individual investors can make or break a stock like Gamestop, investors both large and small are anxious to find actionable insights that will tell them where the market is going, where growth can be found, and what reliable stocks represent a safe harbor of sorts. None of these are easy asks in a financial ecosystem being ravaged by a pandemic, global and domestic sociopolitical unrest, emerging cryptocurrencies, divergent outlooks on trade policy, and the question on every economist’s mind:  what “to do about” China.

 

An investment crystal ball

Sometimes, in economies as chaotic as this one, investors will look to past markets hoping to glean intel on what’s likely to occur next. Others argue that our markets have never faced circumstances like this, and intelligence from the past is baseless. 

While there’s no crystal ball for predicting the future, prognostication is getting closer to reality, at least in one area of analytics. As a patent attorney, I know that patents for innovative products and services require official filing before public use. This means that patent data can be used to give insight on investment opportunities, often before market data in many cases. 

Not exactly as lucid as an image in a crystal ball, patent data still has a pretty reliable record for identifying technological shifts in market direction and industry trends. This in turn can lead to the pinpointing of potential investment opportunities.  

 

A new look at patent forecasting

Originally, investors dismissed patent forecasting as only capable of identifying overall advances in technology. When it came to individual investment opportunities, the evidence wasn’t so reliable, as many start-ups often times failed to leave the gate. 

Prior to the advent of artificial intelligence, no one was able to leverage patent data with other market “tells” such as merger and acquisition candidates or disruptive technologies that had yet to hit the market. At the time, performing such calculations would be expensive and time-consuming to analyze even with commercially available software. 

Still, some investors sensed that patent data could ultimately reveal bankable startups. In some instances, companies would go so far as to pay experts to review thousands of documents to see if any patterns would emerge; this was work that required weeks and months interpretation, often outputting information that was too stale to take advantage of. This process would then have to be repeated with refreshed data, and the cycle would continue, always resulting in predictions too late to practically pursue. 

 

Letting artificial intelligence do the groundwork

Advances in artificial intelligence (AI) and machine learning (ML) has fueled the growth and need in the “art” of patent forecasting. Robust software platforms, leveraging AI’s ability to analyze, filter, and aggregate huge sums of data, from disparate sources, have actually become surprisingly accurate about predicting what industries and specific businesses will emerge from the patent process as investment-worthy winners.

Patent forecasting in 2021 has already affirmed substantial growth in a variety of sectors, from smart vehicles to computing to cybersecurity. Investors, using patent software platforms, are identifying the patent position that will determine who will emerge victorious (and profitable) in these sectors.

Today’s platform can rapidly assess data, account for myriad variables across the entire spectrum of a market sector.  Then, the visualization of this data, in unique ways, allows investors and business leaders to spot the promising trends – all without having to read a single patent. (Though, when diligence calls for it, dynamic, interactive data allows experts and analysts to drill down into full patent content when necessary).   

 

Patent forecasting case study: Edge Computing

By way of example, let’s take a look at edge computing.

In addition to hardware, edge computing platform technologies also include software that enables the truly distributed, low latency analytics required for everything from IoT sensors and V2X wireless communication to the components required to build smart city infrastructure applications.  

Surprisingly, according to current predictions from patent analytics, companies to watch in this sector include disrupters like EDJX, Inc. based in Raleigh, NC.  While patent forecasting data does show big corporate players like Akamai Technologies, Cisco Systems, and Intel as leaders over the long term, their inventions appear to be more evolutionary than revolutionary in comparison to what a startup like EDJX is doing. 

That’s why we predict companies like EDJX – who are innovating in the software for edge computing – will make a big impact in 2021 and beyond.  Many companies will claim to offer edge computing platforms, but just like the cloud-washing over the past decade, most offerings will not provide the true edge compute and scale required for IoT enablement and multi-tenancy solutions. 

 

Patent forecasting in a nutshell

The marriage of big data and analytics is the catalyst patent forecasting has been waiting for. AI and machine learning will make these software platforms an insightful tool for those hoping to identify the bankable winners emerging from the patent office. 


JiNan Glasgow George is Global IP Strategist and CEO of Patent Forecast, creating actionable business intelligence using analyst insight powered by AI and machine learning.

Jinan headshot