SquarePeg is an AI screening tool that enriches resumes, scores & ranks every applicant in your ATS against your criteria, and helps you qualify the right candidates with explainable rationale.
Most teams connect to their ATS and review a ranked shortlist in minutes. Initial ingestion times depend on the volume of applicants in your ATS.
Create a free SquarePeg accountAPI keys for your ATS (Admin recommended for a smooth integration)
Enrichment brings deep intelligence about the candidate and their work history that often isn't found on a resume. This includes most firmographic data, including company industry, size, growth, funding, department growth, and hundreds of other indicators. This allows you to search for things like "show me candidates from high growth VC backed cyber startups
Unlimited applicant screening for one live job at a time. You can enrich, score, run fraud checks, and share explainable shortlists. Once you close that job, you can use SquarePeg on another job.
Upgrade to a paid plan to score multiple live jobs.
No. The free tier is free. Paid plans unlock concurrent jobs.
You can invite multiple recruiters and hiring managers under the same company account. Our pricing is based on usage and concurrent jobs, not per seat.You can use any role, but we recommend roles where you have a high volume of inbound applicants.
The new SquarePeg is rebuilt for AI-powered resume screening, enrichment, scoring, and fraud detection based on professional experience and job relevance. For early stage startups looking for an all-in-one + free ATS please email kahina@squarepeg.ai
It cuts manual resume review, surfaces qualified talent faster, detects fraud and AI-generated resumes, enriches company context, and standardizes evaluation across high-volume roles.
A hybrid stack: frontier LLMs for language reasoning, proprietary scoring algorithms, embeddings for semantic match, enrichment from a 30M-company dataset, and fraud heuristics.
It excludes PII (name, contact info, school names, photos, demographics) and focuses on job-relevant signals like skills, titles, tenure, industries, company attributes, certifications, and outcomes.
By combining stylometric patterns, semantic repetition, timeline and company mismatches, duplicate similarity, and metadata anomalies into a reliable fraud signal. SquarePeg does not filter out GPT-written resumes, it just flags anomalies or templated content.
SquarePeg works across industries and company sizes, but is recommended for companies hiring knowledge workers (white collar) where candidates apply with a resume. Most of our customers are high-growth companies in tech, finance, and healthcare., SquarePeg works best when applicant volume is high, fraud is a concern, or teams are lean.
Many employers choose to disclose that they are using AI to screen resumes. Using SquarePeg actually means every profile will be thoroughly reviewed and matching takes all the context of a resume and candidate’s work history into account, vs a keyword search. provides a transparent rationale and audit logs so you can disclose AI use clearly in your own candidate communications.
Yes. In addition to our free tier, SquarePeg offers a 90 day paid pilot so teams can assess ROI across all of their roles. SquarePeg will provide you with an ROI dashboard during the pilot so you can see key metrics needed for assessing pilot success.
You can disconnect your ATS from SquarePeg at any time, and your data will be deleted within 90 days.
SquarePeg uses a multilayer approach to fraud detection. We check if the candidate’s phone number is registered with a carrier, we look at email address activity, Linkedin profile creation date and connections, work-history validation against a 30M-company dataset, role plausibility, AI generated content detection, and suspicious application patterns. We do not filter out candidates for any one fraud flag, but flag multiple layers that could amount to a candidate being considered fraudulent.
SquarePeg analyzes every applicant using a multilayered evaluation pipeline. First, we enrich each resume with verified firmographic data about the companies in a candidate’s work history—including size, industry, stage, and growth during the years they worked there. We combine this with all available resume signals (skills, job titles, progression, tenure, achievements, industry relevance, and more) and run a deep-context match against the job requirements.Instead of keyword matching, SquarePeg uses structured skills, title, and industry ontologies to understand relationships between skills, the seniority implied by past experience, and whether the candidate’s background aligns with what the job actually needs. Weighting is fully dynamic and adjusts to each employer’s priorities—for example, one role may value industry experience heavily, while another may weigh technical depth or project complexity.Finally, every score is fully explainable. Employers can see exactly why a candidate ranked where they did, which signals mattered most, and how they compare to others in the pipeline.
SquarePeg is designed for high precision and transparency rather than black-box scores. Our screening combines enriched resume data, structured skills and title ontologies, deep-context analysis, and fraud detection to produce rankings that closely reflect the hiring manager or recruiter’s actual requirements. Across customers, recruiters consistently report that our rankings surface the most qualified candidates faster, reduce time spent on low-quality applicants, and identify issues that traditional ATS filters miss.We also provide explainable scoring—every recommendation includes a clear rationale—so teams can verify signal quality themselves. The result is screening that is consistent, auditable, and aligned to your specific role requirements—not just keyword matching, and never a black box.
Yes. SquarePeg is built as a glass-box system with full rationale, audit logs, and strict SOC 2–aligned controls. We conduct regular penetration testing and maintain comprehensive logging across our screening workflows. In addition, SquarePeg undergoes monthly third-party fairness and compliance audits through Warden AI, ensuring alignment with emerging AI-hiring requirements in jurisdictions such as New York City and California.Our approach avoids black-box models, excludes protected attributes and proxies, and provides transparent explanations for every score—making it easier for employers to meet their own compliance, audit, and documentation obligations.
SquarePeg enriches every application with detailed firmographic data for each company in a candidate’s work history—matched to the specific years the candidate worked there. This includes global, GDPR-compliant data on company size, industry, funding history and amount, headcount growth, key products, major news mentions, competitive landscape, and more.By adding verified firmographic context to each role on the resume, SquarePeg gives recruiters a clearer picture of the environments a candidate has operated in—whether they scaled inside a high-growth startup, worked in an enterprise setting, or contributed within a niche industry. We continuously expand the categories of enrichment to give teams deeper, more accurate context beyond what appears on the resume.
Through embeddings similarity, structural and timeline matching, company-history overlap, and metadata fingerprints ~ even when names or formatting differ.
Data is stored only for screening, never used to train models; customers own their data and can request deletion at any time, with SOC 2-aligned security practices.
SquarePeg’s Chrome extension adds a real-time intelligence layer directly on top of your ATS—no engineering work required. Once installed, it displays applicant scores, fraud indicators, enriched company data, skills analysis, summaries, and duplicate checks in a clean side-panel next to your ATS UI.Whenever you open a job, you’ll see a stack-ranked list of candidates, and clicking into any applicant reveals SquarePeg’s full explanation of how their experience aligns with the role. The extension deploys in minutes and gives recruiters the power of SquarePeg’s screening, enrichment, and analysis without ever leaving their existing workflow.
Yes. Hiring managers can be invited into SquarePeg to view applicant scores, explanations, shortlists, enrichment, and fraud indicators—all in the same interface recruiters use. This helps teams stay aligned on what “good” looks like for a role, reduces back-and-forth on candidate quality, and gives hiring managers a clear, transparent view of why candidates are ranked the way they are. Many teams use SquarePeg collaboratively so both recruiters and hiring managers can make faster, more informed decisions.
When new candidates apply to live role(s), they are enriched and scored as they arrive so your ranked list stays current.
SquarePeg retains data only as long as needed for screening and account usage. Admins can request deletion of data and revocation of ATS access at any time. SquarePeg deletes data within 90 days once your ATS is disconnected.
Admin permissions make setup faster. You can still create an account, but an admin may need to approve access.
SquarePeg has a 2-way sync with the ATS so all actions taken within SquarePeg are reflected in the ATS and vice versa. SquarePeg does not populate ATS fields, but our chrome extension provides all SquarePeg data that can be viewed while working inside the ATS.
After connecting your ATS, SquarePeg begins importing your candidates and job data. If scores are not appearing yet: Confirm that the initial sync has completed. You can view the last sync time from your main dashboard or your settings. If needed, run a manual sync.Make sure the job has requirements set. Scores cannot be generated until you add and save requirements for the role.If candidates recently applied, allow up to a few minutes after a manual sync for scores to process.If you have confirmed all of the above and still do not see scores, contact Support and we will review your ATS connection.
Open the flag details to review the evidence. Dismiss if acceptable and add a note for your team.
Start by opening the candidate’s profile to see which requirements drove the score. If the emphasis feels off, adjust your weights (skills, titles/seniority, experience, industry) and rescore. If SquarePeg enriched a requirement incorrectly, you are able to submit feedback directly to our product team in-app.
SquarePeg automatically syncs with your ATS every three hours. If you see candidates in your ATS that are not yet visible in SquarePeg, check the timestamp of your last sync. You can run a manual sync at any time from the main dashboard or from your settings page. Once the sync is complete, SquarePeg will update candidate visibility and stage alignment based on the information in your ATS.
Scores are determined by the requirements you set. If you are not seeing much variance between scores, that is a great indicator to add more requirements!
SquarePeg will honor any automations or workflow rules you have set in your ATS. When you update a candidate stage in SquarePeg, we push that update back into your ATS instantly and trigger any connected actions associated with that stage. This includes notifications, movement to later pipeline steps, and any ATS level automations your team has configured.
AI can be used in hiring in many different ways. It supports everything from sourcing and scheduling to assessments, interview assistance, and onboarding automation. For recruiting teams specifically, AI is especially valuable in screening, where it can read and structure resumes, understand skills in context, detect fraud or risk signals, and compare each applicant to the requirements of a role.Tools like SquarePeg use enriched resume data, structured skills and title ontologies, fraud detection, and transparent scoring to help recruiters and hiring managers identify aligned candidates more quickly and with clearer rationale.
Glass-box AI shows the underlying signals, data, and reasoning behind each recommendation so humans can review, understand, and override decisions. Black-box AI provides outputs without explaining why, making it harder to audit or trust. SquarePeg uses a fully glass-box approach: every score includes clear rationale, evidence, and audit logs so teams can see exactly how an applicant was evaluated.
Yes. AI systems can reflect or amplify bias if the underlying data or rules contain biased patterns. That’s why independent audits, strong guardrails, and human oversight are critical in hiring. Companies like SquarePeg mitigate these risks by excluding protected attributes and proxies from screening, operating within strict SOC-2–aligned controls, and undergoing monthly third-party fairness and compliance audits through Warden AI to help ensure responsible, compliant use.
AI systems analyze structured signals—such as skills, experience, job titles, tenure, and relevant outcomes—and use rules or models to assess how closely a candidate aligns with the criteria defined for a role. While many tools rely on simple keyword matching or generic LLM outputs, SquarePeg reads deeper context, enriches each resume, and evaluates how skills and experience connect so strong candidates aren’t overlooked.Importantly, AI does not make hiring decisions. In tools like SquarePeg, recruiters or hiring managers set the requirements and always remain the final decision-makers. The AI provides matching insights, rankings, and rationale to support screening, but humans review, interpret, and decide which candidates move forward.
While AI is great at repetitive tasks like reading large volumes of resumes, it takes a human like you to build trust, understand human context, and close candidates. Recruiters provide judgment, relationship-building, and strategy that AI can’t replicate.Think of AI as a copilot, not a replacement. Tools like SquarePeg handle the heavy lifting so recruiters can focus on the human parts of hiring that matter most.
AI can make hiring fairer by applying the same criteria to every applicant, using only job-relevant signals, standardizing evaluation, and removing off-limits or biased data. Unlike manual review—which often involves quick scans or keyword searches—AI can read and analyze every candidate in the pipeline, using the full context of their skills, experience, and work history.When paired with transparent explanations and clear audit trails, this consistency helps reduce subjective variation and makes it easier to detect and correct bias. Tools like SquarePeg strengthen this further by excluding protected attributes and proxies, reviewing all candidates with full contextual analysis, and providing explainable scoring to support more objective and equitable hiring decisions.
You should look for a tool that is accurate, transparent, and fits seamlessly into your existing tech stack without requiring heavy implementation. It should be fast, affordable, and clearly best-in-breed at what it does—not an unfocused “all-in-one” platform that spreads itself thin. A strong AI hiring tool should demonstrate real ROI in the first week, by reducing time spent on low-quality applicants and surfacing top talent quickly.It should also provide clear explanations of how it works, give you control over criteria and weights, maintain strong security and privacy protections, and undergo ongoing bias and fairness checks. And importantly, it should allow you to override any recommendation while evaluating every applicant with full context, not relying on keyword scans.Tools like SquarePeg meet these standards by offering deep contextual screening, transparent scoring, SOC-2–aligned controls, monthly third-party audits, and instant value the moment it’s deployed.
AI can analyze every resume, surface patterns no human could catch at scale, detect fraud, and objectively match candidates to job requirements. It brings consistency, speed, and data-driven insights that dramatically improve the early stages of hiring.But hiring is more than screening. Humans set the strategy, define what “great” looks like, and adjust criteria as business needs evolve. They interpret nuance, assess culture and team fit, build relationships, persuade top candidates, and ultimately make the final decision.AI tools like SquarePeg handle the heavy analytical lift so recruiters and hiring managers can focus on the human work of hiring: judgment, communication, trust-building, and long-term talent decisions.
The best AI tools for resumes are purpose-built for top-of-funnel evaluation, not generic LLM wrappers or basic keyword filters. They should enrich and structure resume data, interpret skills and experience in context, let you control criteria and weights, provide clear and explainable rationale, and maintain a full audit trail for compliance and fairness reviews.Many ATS platforms—such as Ashby, Workable, and Greenhouse—offer lightweight internal AI features, but they typically do not include deep firmographic enrichment, fraud detection, duplicate detection, or fully transparent scoring. For teams handling high applicant volume or requiring stronger accuracy and compliance, it’s usually more effective to add a best-in-breed tool that integrates with your ATS.SquarePeg is the most robust option in this category, and other strong tools include Covey, Endorsed, Gem, and Eightfold, depending on your workflow and priorities.
Keyword filters only search for matching words or phrases—they don’t understand context, seniority, relevance, or whether a candidate actually meets your requirements. A dedicated AI screening tool goes much further: it enriches and structures resume data, interprets skills and experience in context, scores candidates against your defined criteria, flags fraud or duplicate profiles, and provides transparent explanations for why each applicant is ranked the way they are.Tools like SquarePeg help ensure you’re evaluating every candidate fairly and accurately instead of relying on keyword hits that can miss strong applicants or surface unqualified ones.
SquarePeg is a best-in-breed, top-of-funnel screening tool designed to evaluate every applicant with speed, accuracy, and full transparency. Unlike generic LLM wrappers or ATS keyword filters, SquarePeg enriches each resume with deep firmographic data, analyzes skills and experience in context, scores candidates against your specific criteria, and detects fraud or duplicate profiles.Most screening tools provide limited or opaque scoring. SquarePeg provides a glass-box rationale, showing exactly why each applicant is ranked where they are so recruiters and hiring managers can trust—and audit—the results. It integrates directly with your ATS and focuses exclusively on delivering the most accurate, explainable, and compliant resume screening experience.
ChatGPT can summarize or rewrite resumes, but it is not built for compliant or auditable resume screening. It does not enrich company data, apply consistent scoring rules, detect fraud or duplicates, or integrate with an ATS. It also lacks the governance, repeatability, and fairness controls required in a real hiring workflow.Dedicated tools like SquarePeg provide the structure ChatGPT cannot: standardized enrichment, transparent scoring, recruiter-defined criteria and weights, fraud checks, audit logs, and seamless ATS integration—so applicant evaluation is accurate, consistent, and compliant.
SquarePeg is a strong fit if your team works inside one of our 50+ ATS integrations, handles high applicant volume, and needs more than basic keyword search or GPT-style summaries. It’s built for teams who want deep resume enrichment, accurate and transparent scoring, fraud and duplicate detection, and rankings they can confidently defend to hiring managers and compliance teams.If you want to see how it performs on your actual pipeline, you can test SquarePeg on a live role through our free tier.
