To find untapped value in unstructured data by building solutions that help companies innovate, grow, increase profit and manage risk.
Our Story
Speciate AI was founded by former leaders of PwC’s global data analytics consulting team. Our experience advising Fortune 500 companies on how to apply advanced data and analytics techniques gave us three insights that led us to launch Speciate AI. First, companies have barely begun to tap unstructured data, which accounts for over 90% of the total data in the market. Today they spend 90+% of their data and analytics budget on managing and analyzing their structured data in data warehouses and data marts. We think this investment mix needs to shift. Second, companies are just scratching the surface on applying the power of artificial intelligence which is well suited to extract value from massive unstructured data sets that include text, images, audio and video formats. We think AI applications will become pervasive. Third, the economics of analysis can be radically transformed by creating AI driven solutions that analyze unstructured data to solve a range of business problems. We launched Speciate AI with the aspiration to use the power of artificial intelligence to deliver 100 to 1,000x the analysis for one- tenth of the cost.
The Speciate AI Difference
Advisory Mindset
We have experience advising senior executives and practitioners on how advanced data and analytics techniques can solve complex business problems, creating business cases to justify the investment and executing plans to provide tangible benefits on an ongoing basis.
Agile Approach
We understand that creating value with data and analytics is not a one and done proposition. We use an agile approach as we work with our customers to demonstrate the value from our solutions, identify needed changes, and quantify the potential return, prior to building at-scale solutions.
Data Synthesis
We continuously add and integrate new data to our exclusive and non-proprietary data sources that include text, audio, images and videos. We expand our data ontology that includes representations of companies, products, and customers so you always have the most current market view. We apply the latest AI techniques to synthesize the data into actionable insights as opposed to overwhelming you with more data.
Enthusiasts Network
We use our exclusive partnerships with media companies, academic communities and other providers to form a network of “Product Enthusiasts” that companies can tap to provide deep insights for market research, product development, experience design, go-to-market plans and post launch changes. We truly allow companies to have an ongoing dialogue with informed customers that can provide novel insights.
Our Team
We are a team of multi-disciplinary experts that combine data engineering, data science, solution design and development, and analytics advisory skill sets to provide you innovative data and AI solutions that give you the actionable insights that matter most.
Paul Blase is a co-founder of Speciate AI which is spin-out from tronc. Formerly Paul was the managing partner of tronc’s AI and data solutions division responsible for building a portfolio of businesses and products that monetize data. Prior to that Paul was PwC’s U.S. and global analytics advisory leader responsible for capturing the market opportunity associated with helping it’s clients use advanced analytics and data techniques and technologies to improve the performance of their businesses across. During his time at PwC, Paul designed and launched PwC’s U.S. and global analytics and data operating model and managed investments across a team of nearly 1,700 practitioners with deep skill sets in data and analytics. Paul led the creation of a portfolio of analytic apps and launch of PwC’s global Analytic Apps Marketplace to provide analytics solutions to its clients. Prior to being acquired by PwC, Paul was a Managing Partner at Diamond Management & Technology Consultants where his responsibilities included leading its cross-industry Service Lines, insurance practice and enterprise practice. Paul’s speaking and publications forums include the Chicago Council of Global Affairs, Palo Alto Venture Forum, Oracle Openworld, Wall Street Journal, Financial Times, Bloomberg, World Economic Forum, Corinium CAO Forum, AI World, and Forbes. Paul holds an M.B.A from M.I.T. Sloan School of Management with a focus on new product & venture development and a B.A. double major in Economics and Mathematical Methods in the Social Sciences Honors Program.
Kate Besser
CMO | Co-Founder
Kate Besser is Director of Market Development at Speciate AI. Prior to joining Speciate AI, Kate was the director of product and market strategy for tronc’s AI and data solutions division. Before joining tronc, Kate was a member of the analytics advisory team at PwC providing data-driven expertise and solutions to clients primarily in the private equity, industrial products, aerospace and defense sectors. Kate also served in the U.S. Navy as a division officer on the USS Pearl Harbor and as an operations officer at Commander, Naval Surface Forces.
Kate holds an M.B.A. from University of Chicago Booth School of Business with concentrations in econometrics and statistics and entrepreneurship and a B.S. in quantitative economics from the U.S. Naval Academy.
Spencer Allee
Lead Data Scientist | Co-Founder
Spencer is the Lead Data Scientist at SpeciateAI. He has spent his career building data-driven solutions for Fortune 500 clients and he led PwC’s Analytics Innovation Accelerator, an R&D team focused on commercializing machine learning and big data technology. He has worked across a number of industries including insurance, banking, digital media, consumer electronics, pharmaceuticals, and others. He holds a BA in Economics with Distinction from Yale University.
Eva Huang
Senior Data Scientist
Eva Huang is a Senior Data Scientist at Speciate AI. Prior to joining Speciate AI, Eva was an associate director of data science at Annalect building sentiment analysis and marketing sub-segmentation models for clients in the food and beverage industry. Eva has also worked as a principal data scientist at Capital One Financial, leading the validation of various credit card risk and fraud models.
Eva holds an M.S. in Statistics from the University of Virginia and a B.S. in Life Science from Peking University.
