RecruitBot, a recruitment platform, announced raising $8.2 million in additional seed funding to expand its AI-powered recruitment software. The investment round was led by Slow Ventures, with participation from SNR, OCA, Freestyle and Parade.
The company aims to empower recruiters by improving talent sourcing and expediting the hiring process through AI and machine learning (ML).
RecruitBot said its advanced AI algorithms enable the platform to comprehend recruiter preferences and display increasingly relevant candidates from its qualified database of 600 million profiles. Additionally, the platform facilitates personalized, automated email campaigns to candidates on behalf of hiring managers.
The company said that unlike traditional hiring platforms, RecruitBot is equipped with filters, including support for diversity, equity and Inclusion (DEI) initiatives, combined with machine learning. This allows for rapid identification of candidates ideally suited for a role.
“Most tools only solve part of the problem: finding different/relevant candidates, reaching out to those candidates, interacting with your ATS, sourcing on LinkedIn. Our platform solves all of these problems in a single product — it’s a paradigm shift from the standard ‘recruiting funnel’ to a ‘recruiting flywheel,’ where continued sourcing for similar roles becomes more effective over time,” Jeremy Schiff, CEO and founder of RecruitBot, told TechForgePulse. “Our machine learning algorithm improves relevancy, [and] automated personalized outreach and analytics improve response rates.”
Schiff explained that based on previous reviews, the platform’s proprietary machine learning algorithms analyze and identify candidates who closely match the desired criteria. This enables users to discover candidates more highly suitable for specific roles,.
He said the platform enables recruiters to review five times fewer candidates while still finding relevant matches.
This latest funding round builds upon RecruitBot’s growth in 2022 and its previous $3 million pre-seed funding round. The company has now raised a total of $11.2 million since its launch.
Streamlining recruitment through AI
Many companies struggle to identify the right candidates and find effective approaches to engage them.
According to RecruitBot’s Schiff, recruiters often face excessive workloads and limited resources. The burden of managing multiple sourcing tools, an outreach tool, an applicant tracking system (ATS) and a customer relationship management (CRM) system can be overwhelming, leading to suboptimal utilization of these tools.
“Without one place to find and engage with candidates, there are problems ranging from ensuring recruiters don’t double-engage the same candidate to data integrity for analytics — let alone fancier things like repurposing the recruiter’s decisions for machine learning,” Schiff told TechForgePulse. “You can’t provide an effective search and recommendation tool without clean data and deep integrations between these different problems.”
RecruitBot said it tackles these pain points by offering a solution encompassing sourcing, outreach and analytics in one top-funnel platform. The platform’s machine-learning capabilities allow companies to customize their candidate searches based on skills, experience and other criteria through a single, scalable tool.
“The value of RecruitBot’s machine learning is that it personalizes the results for a specific position at a specific company. What RecruitBot focuses on will differ depending on a recruiter’s or hiring manager’s decisions. In some cases, there are obvious things it will focus on, like education or job titles,” explained Schiff. “As it learns more, it may focus more on skills, where it can understand that this person is great for the job, even if they don’t have the right title.”
He said that the platform possesses the ability to comprehend the intricate meanings associated with words such as “service leadership,” “ownership-oriented” and “numbers-driven.”
Schiff stated that the company plans to use the funding to enhance its AI capabilities and expand its customer base through sales, marketing and customer success investments. This strategic allocation of resources aims to empower more customers and fuel the development of additional AI features in the coming months.
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