Our first chat with Speciate founder Paul Blase revealed the history of our AI-powered market monitoring solution. Our discussion outlined how Speciate came to be, who it serves, and what it means to be truly fueled by artificial intelligence. We also discovered that the potential of unstructured data is immense. This kind of data is a vast realm containing hidden, highly valuable, and novel insights that has potential to upend the way competitive intelligence services is conducted.
But with all of its forms – structured, semi-structured, and unstructured – finding, organizing, and analyzing thousands upon thousands of data to find real nuggets of insight that drive true strategic decisioning can become arduous, exhausting, and ultimately futile, especially for smaller teams with limited resources.
Engaging in competitive intelligence projects can prove to be daunting, especially with limited analyst resources and organizational capacity to execute on intelligence projects. But the value is always clear – gaining an edge over your competition. That’s what helps to make Speciate AI so valuable – our market monitoring solution easily scans and finds highly relevant information through an AI-powered system that accesses billions of data points, and filters through the noise to find the most impactful data and ultimately the insights that companies needed to gain the upper hand.
In this second chat, we dive deeper into the power of Speciate and how our data relationships and analysis process can unlock insights from a world of unstructured data. Find details on these topics and more in the Q&A below.
Paul: Yes. Speciate is an AI-powered system that uses numerous algorithms to scan billions of data points like media articles, social media, company financial guidance and performance, academic papers, filed patents and more.
Now, keep in mind that all of these sources publish new pieces every single day… which amounts to billions of statements that we can analyze. To put that into context, 7.5 quintillion bytes of data is generated each and every day – enough to fill over 100,000 Libraries of Congress – and roughly 90% of it is unstructured. Not only will this number continue to grow over time, but more and more of it will be unstructured.
Paul: Value can be defined in many ways but is ultimately based on the type of question we are trying to answer for a customer. When a customer comes to us and asks us to help solve specific issues – from identifying emerging technologies and company investments to monitoring companies and their products – we implement our world-class ontology.
From there, we perform analysis to determine what value is created by our algorithms that produce specific metrics, and links to media and influencers to inform insights – all from unstructured data. The Speciate AI ontology provides a structure for grouping data into categories and relationships of attributes. These categories and attributes create a first filtering mechanism to identify topics and connections in the data that are available.
Paul: The idea is very simple: all of the data sources we use are publicly available and/or can be procured from third party vendors. The proprietary data pipelines we build to access that data is what makes us unique and highly valuable. These pipelines are integrated into our ontology and metrics we produce to deliver insights. It’s this unique relationship between data sources and algorithms that gives Speciate its gusto.
Paul: Within the first couple of years, Speciate’s primary challenge was to identify product-market-fit for the multiple types of analysis and insights we could produce. We eventually landed on market landscape monitoring as a solution within a competitive intelligence framework.
Typically, the customers we work with want a wide net cast over their market so they can keep tabs on what is happening with competitors, customers, emerging technologies and macro trends. Over time, we observed our customers and their use of our analysis, and have evolved the way we deliver insights into more standardized lenses, data filtering, collaboration with top-tier experts and more to fine tune the capabilities of Speciate.
Paul: there are several aspects that truly separates Speciate AI from other services and solutions in the market today:
Paul: I was leading PwC’s US and Global Data & Analytics Practice in 2015 when AI piqued my interest. Our Innovation Lab worked with leading academic labs from around the world – University of California San Diego, Carnegie Mellon University, Fraunhofer Institute (Germany), AStar (Singapore), and others.
I saw firsthand the explosion of data that was collected in cases where algorithms were being trained to collect highly specific information. Some algorithms collected highly specific video, like wildfire paths to identify impact of material types and topography on burn patterns. Another had the ability to reliably identify people and objects in images. It was so fascinating to see the impact that AI could bring. I loved that it could see the unseen patterns in data and extract meaning out of massive data sets that couldn’t be processed at scale. It was all uphill since then.
Paul: What will be exciting to see over the next year is how we will continue to expand our market leading ontology to add more structure to the terabytes of unstructured data we process. It will expand the types of automated insights we can produce for our customers, including identifying where customers have pain points and unmet needs not addressed by existing products.
Our ontology will come to understand the concept of what a product is and what a customer is, which is really powerful as our clients are always interested in what customers think about their products and how they can improve them.
Are you curious to learn more about how Speciate AI’s market monitoring solution can help you gain an advantage over your competitors in a fraction of the time? Schedule a demo today and be amazed by all that Speciate’s competitive intelligence solution can offer.