SquarePeg has raised a $3.5 million seed round led by Next Frontier Capital, with participation from Acadian Ventures, Bread & Butter Ventures, and Silicon Road Ventures, to refine its AI-driven candidate evaluation platform. Designed for mid-market companies and lean recruiting teams, SquarePeg integrates seamlessly with applicant tracking systems (ATS) to enhance resume screening, enrich candidate profiles, and reduce reliance on keyword matching. The platform leverages AI and large language models (LLMs) to provide transparent, contextual hiring insights, ensuring fair and efficient candidate selection. SquarePeg aims to redefine talent acquisition by automating tedious tasks while maintaining ethical and explainable AI practices.

Here is the official introduction to SquarePeg, please read on!



Over the past 18 months, our team at SquarePeg has spent a lot of time talking to recruiters, TA leaders, and hiring managers, all who are facing the same struggle: managing a mass influx of resumes, manually screening thousands of applicants, and trying to identify the best fit for their open roles. And all of this is happening while HR teams are shrinking and hiring demands are getting more precise.

Since building our all-in-one recruiting platform for startups in 2022, a pattern started to emerge: mid market companies coming to SquarePeg looking for a way to score their applicant pool, enrich their ATS candidates, and help their lean team of recruiters manage more open jobs.

We started a series of deep conversations with recruiters about why their existing tech stack was failing them, all while they were being asked to “do more with less.” We set out to build a platform that natively integrated with their ATS and helped them score, evaluate, and process applicants at lightning speed. We listened to concerns about not missing qualified candidates due to keyword mismatch, the need for truly unbiased matching, and how to make better selection decisions by enriching candidate resumes with useful contextual data.

This most recent round of funding has allowed SquarePeg to build a mid market product that truly understands the recruiter’s  pain and works within their ATS workflow. One that cuts through all the noise and is built alongside recruiters, for recruiters.

Since we closed our round, we’ve been heads down in build mode, testing our product with customers and building out a waitlist of companies ready to adopt AI tools that improve recruiting outcomes.

The Funding News

To bring this product to market and help recruiting teams 10x their impact without adding additional resources, we’re proud to announce that we’ve closed a new $3.5 million in funding. This investment will help us deliver on our mission to turn noisy, unstructured applicant data into recruiting intelligence that saves time and improves hiring outcomes.

We are lucky to have an incredible group of pre-seed and seed investors who understand that even in a crowded HR tech landscape, there is demand for systems of intelligence that help find signal in the noise.

SquarePeg’s seed round was led by Next Frontier Capital with participation from Acadian Ventures, Bread & Butter Ventures and Silicon Road Ventures. We’re also fortunate to have support from existing investors Full Circle, Vitalize, Loyal VC, and Yokohama Ventures.

Next Frontier, Bread & Butter, and Silicon Road Ventures bring deep B2B SaaS operational expertise, while Acadian, Vitalize, and Full Circle are laser focused on the Future of Work and HR Tech. We are excited to build alongside some of the best HR Tech startups in the world like TechWolf, SmartRecruiters, Oyster, and Compa to uplevel the capabilities of HR teams.

Bringing Glassbox AI to Lean Recruiting Teams

One thing we hear repeatedly from Talent Acquisition leaders and Chief People Officers is a desire to embrace AI in an ethical and explainable way. Recruiting is rife with manual processes suited for automation–but there are legitimate concerns that when software evaluates humans, viable candidates will be unfairly rejected.

That’s why a huge focus of our product roadmap post-raise is using AI to help explain why a candidate is a certain match with a job, bringing in contextual data that a recruiter may not have from a 30 second resume scan. SquarePeg takes into consideration skills, job titles, industries, tenure, and other available data and uses LLMs to provide context and explanations behind each match at a granular level - so even if a recruiter is unfamiliar with a skill or a company, SquarePeg can provide reasoning in place of keyword matching.

This is an essential feature as employers get bombarded with thousands of resumes, and are ill-equipped to separate robo-apply, fake profiles, and legitimate qualified applicants. Moreover, SquarePeg plans to bring this technology to the entire ATS, identifying qualified candidates who’ve applied to past roles with their updated job history, as well as top passive profiles.

As we build these products out loud with customers and design partners, we’re big believers that the advancement of LLMs provides an incredible opportunity to bring better matching and intelligence into the chaos that is top-of-funnel recruiting.