Whizbang! Labs
Whizbang! Labs is a company.
Financial History
Leadership Team
Key people at Whizbang! Labs.
Whizbang! Labs is a company.
Key people at Whizbang! Labs.
WhizBang! Labs was a Provo, Utah-based technology company specializing in information extraction software using advanced machine learning to search, classify, and extract data from websites and documents. Founded in 1999, it developed products like the job recruiting site FlipDog.com, which gained recognition as a Top 100 site by PC Magazine in 2000[3][5]. The company raised $30M in funding but struggled to find a profitable business model amid cuts in capital expenditures for expensive tech, leading to its shutdown in May 2002 with layoffs of about 70 employees[1][3][5].
WhizBang! Labs was founded in 1999 by Robert Sherwin (CEO), Berkeley Geddes, and Dallan Quass in Provo, Utah, with an additional research lab in Pennsylvania[3]. The idea emerged in the late 1990s dot-com boom, focusing on machine learning for information extraction; a pivotal early success was launching FlipDog.com in 2000, which quickly earned acclaim[3]. Despite raising $30M from investors including Inxight Software and HP, the company faced mounting challenges post-dot-com bust, undergoing multiple layoffs and cost-cutting before CEO Sherwin announced closure in May 2002 to protect assets and provide severance[1][3][5].
WhizBang! Labs rode the late-1990s wave of machine learning and internet data extraction, coinciding with the dot-com expansion where tools for web scraping and job search were emerging[3][4]. Timing was critical: post-2000 bust, enterprise budgets slashed "expensive" capital tech, dooming even strong products amid market forces favoring cheaper alternatives[3]. It influenced Utah's early tech ecosystem as a Provo startup hub player, highlighting risks in AI-adjacent software during economic shifts, and its FlipDog.com contributed to evolving online recruiting before giants like Indeed dominated[3].
WhizBang! Labs ceased operations in 2002, with no active revival evident; efforts focused on selling its software assets and relocating talent rather than continuation[3][5]. Trends like cost pressures on enterprise AI persisted, shaping modern data extraction tools toward affordability and scalability. Its legacy underscores early machine learning promise in a volatile market, tying back to a "splash" maker that couldn't sustain amid bust— a cautionary tale for today's AI startups balancing innovation with economics.
Key people at Whizbang! Labs.