Sensea

Joanna Riley founded Sensea in September 2017 with a clear mission: to revolutionize enterprise hiring by removing unconscious bias and leveraging predictive AI. Her insight came from recognizing that traditional hiring methods—scrolling through LinkedIn, manually filtering resumes—are inherently flawed and one-dimensional. "Every single technology in the world today, when you're finding people, you can only look at them one-dimensionally," she explained. She was inspired by Trulia's multi-dimensional approach to real estate search and applied that thinking to talent acquisition.

Riley launched the Sensea SaaS platform in July 2018, roughly a year after founding the company. Her technical co-founder, the CTO, brought 20 years of experience building high-frequency trading platforms—systems that analyze massive datasets and make predictive decisions under extreme pressure. He assembled a distributed team across San Francisco, Florida, and Romania, leveraging data science talent that understood complex pattern recognition at scale.

The core product aggregates data from over 2,500 different sources on more than 500 million people globally, creating "golden records" that look beyond surface credentials. Instead of just seeing "Stanford + Google," Sensea's AI could identify that an athlete's discipline matters more than the school, or recognize career trajectory patterns that predict high performers before they're obvious to humans.

Riley executed a smart customer acquisition strategy: she strategically selected companies for a customer advisory board, positioning them as "integration sponsors" in exchange for favorable terms. This meant beta customers converted to revenue-generating contracts in 2019, by which time she had already proven product-market fit. By the time the interview was recorded (70 days after platform launch), Sensea had onboarded 40 enterprise customers—an impressive early traction signal.

Revenue scaled to between $50-100k per month in the first 70 days, putting the company on a $600k-$1.2M annual run rate. Riley's pricing strategy was dual-tiered: a seat-based model ($3,500/year per recruiter seat, typically 10-50 recruiters per client) and a premium role-based SaaS model that automated sourcing, engagement, and interview coordination (ranging from $50-100k per role initially, scaling to multi-hundred-thousand-dollar contracts). She acknowledged one early mistake: raising funding in July/August when VCs are unavailable. She corrected course, got her lead investor in September, and closed the seed round by month-end.

One lesson: she initially wanted to announce a larger seed round but held back to build momentum first. Her team composition reflected product focus—roughly 90% of her 35-person team worked on technology and product, enabling aggressive feature roadmaps through Q1.

Sensea closed a seed round "north of $5 million"—larger than typical seed rounds in the San Francisco market. Riley projected 3-5x growth in revenue over the next 12 months from her December baseline. The company had zero customer churn to report at this early stage, and she aimed to keep annual gross churn below 10% long-term. Her product roadmap was packed: automated competitor analysis, stage-based company matching, and automatic candidate engagement that would make the hiring process feel "magical." At 36 years old, having already built and scaled companies before, Riley was leveraging her experience and investor confidence to scale Sensea into an enterprise AI recruiting platform.