Brainspace Aims to Harness “Collective Intelligence” of Businesses
Dallas — Software can do a lot of things, but can it read between the lines?
That human ability to look for context and the sentiments that are not explicitly stated is the next frontier in “semantic search,” says Dave Copps, the founder and CEO of Brainspace, a machine-learning software startup. Current information-search techniques rely heavily on keywords, he explains.
“That’s the flaw of search in general,” Copps says. Semantic search “is about concepts, and thoughts, and ideas. The word ‘Java’ at Oracle means something different than java at Starbucks.”
What Dallas-based Brainspace says it does is take the internal data generated by a company—the e-mails, memos, strategy plans—and creates a “collective intelligence” of the company. Brainspace takes the information in this digitized “brain” and produces a navigable map, which it calls a “wheel,” that organizes the information into clusters.
Brainspace started in 2005 as Pure Discovery (Brainspace was the name of the product then). Since then, the company has grown to about 50 employees, has raised about $30 million in funds, and counts household names such as Deloitte and PricewaterhouseCoopers as clients. Copps says that as customers like these add to and organize the information in each company’s individual “brain,” Brainspace’s software learns from those changes.
As the collection of digital data on how we work and live continues to grow, software companies like Brainspace are working on making the data more useful through analytics, artificial intelligence, and machine-learning techniques. For example, in 2014 Google acquired London-based Deep Mind Technologies, while Facebook runs a program called FAIR—Facebook AI Research. IBM Watson’s cognitive computing program has a significant presence in Austin, TX, where a small artificial intelligence cluster is growing.
One of those Austin companies is Lucid, which is using artificial intelligence software to give computers more human-like reasoning abilities, to answer not just “What?” but also “Why?” and “So what?”
Copps’s interest in software and making corporate search better stems from a background that includes a degree in industrial anthropology from the University of North Texas in Denton, TX. He got into semantic search, founding and selling a software company, Engenium, to Marsh & McLennan 10 years ago for $27 million.
“I thought, what if I could connect the concepts and thoughts and ideas of a company and create that as an asset?” he says. “Having an engine that can understand your data and build that into an intelligence that everyone can use is a real advantage.”