RippleMatch

RippleMatch is an early-career recruiting platform that sources students and recent graduates for employers' roles, ranks applicants with a 0-100 Fit Score built from criteria the recruiter configures, and adds verified skill badges, applicant review, interview scheduling and campus-event tools.
SourcingScreeningScheduling

HireAIScore rates RippleMatch 46 out of 100 (grade F, Substantial gaps) under rubric v1.0, last reviewed September 25, 2026. RippleMatch ranks 41 of 86 vendors rated in Candidate sourcing AI, against a category average of 46. That score is drawn from 42 evidence items across 7 rubric criteria for RippleMatch — 35 with a cited source, 7 recording that nothing was located.

Score breakdown

RippleMatch, criterion by criterion

Each rubric criterion is scored out of 100 on the cited evidence, then weighted into the total.

Weighted contribution shown to the right of each bar.

  1. Article 11 Technical Documentation

    Weight 20% · avg 48

    46

    +9.2

  2. Bias Audit Transparency

    Weight 18% · avg 40

    53

    +9.5

  3. FRIA Support

    Weight 15% · avg 31

    27

    +4.0

  4. Data Governance Disclosure

    Weight 15% · avg 53

    50

    +7.5

  5. Human Oversight Design

    Weight 12% · avg 56

    57

    +6.8

  6. Post-Market Monitoring

    Weight 12% · avg 40

    37

    +4.4

  7. Customer Documentation

    Weight 8% · avg 57

    60

    +4.8

Total weighted score

46.4(rounded to 46 for display)

Category avg is the mean raw score on that criterion across the 86 Candidate sourcing AI vendors in scope of this rubric, this one included.

Strongest criterion

Customer Documentation

60raw / 100

Contributes 4.8 to the total. 60 against a 57 category average.

Weakest criterion

FRIA Support

27raw / 100

Contributes 4.0 to the total. 27 against a 31 category average.

Cited evidence

The evidence behind the score

Every score is backed by at least one cited piece of evidence. Open a criterion to see what was found, when, and where.

Download diligence record

Evidence ledger

Items
42
Documentation
23
Audit report
3
Public statement
9
Absence
7
With a source URL
35 of 42
Source hostnames
8
Fewest items
2
FRIA Support

These figures measure how thoroughly RippleMatch was reviewed, not how RippleMatch performed — an absence row, recording that nothing was located, is counted like any other item.

Article 11 Technical Documentation

8 items46

Bias Audit Transparency

6 items53
  • Audit reportCaptured Sep 25, 2026

    BABL AI's NYC LL 144 public summary, dated 27 June 2024, covers the RippleMatch Fit Score. It verifies RippleMatch's own January 2024 scoring-rate testing on data from January 2023 to January 2024, reports gender, race/ethnicity and intersectional impact ratios (the lowest is 0.854, for Asian applicants) and rates every section as a pass. The summary can be downloaded from the AEDT Bias Audit link in the site footer.

    https://8139278.fs1.hubspotusercontent-na1.net/hubfs/8139278/RippleMatch%20babl%2006.27.2024.pdf

  • Public statementCaptured Sep 25, 2026

    A February 2023 press release announces an earlier babl.ai audit, published 5 January 2023, that used more than 170,000 applications to test for race and gender disparities; the full report was available only on request.

    https://www.prnewswire.com/news-releases/ripplematch-passes-bablai-bias-audit-unanimously-301736884.html

  • Public statementCaptured Sep 25, 2026

    The Trust & Security page says RippleMatch works with babl.ai every year, yet names June 2024 as its latest audit and offers the full report only on request.

    https://ripplematch.com/trust-security

  • DocumentationCaptured Sep 25, 2026

    The primer says RippleMatch neither collects nor infers applicants' race, ethnicity or gender, but the BABL summary says the audited demographics were self-declared by applicants to RippleMatch during the application process.

    https://resources.ripplematch.com/artificial-intelligence-machine-learning-bias-mitigation-compliance-primer

  • Public statementCaptured Sep 25, 2026

    BABL AI's homepage shows an undated testimonial from a RippleMatch engineering manager describing an ongoing audit relationship for the platform.

    https://babl.ai/

  • AbsenceCaptured Sep 25, 2026

    As of 25 September 2026, no audit newer than June 2024 appears on the trust page, the AI for Good page, the help-center primer or the homepage footer. The 2024 audit covered only the Fit Score, for race/ethnicity and gender. It did not cover the machine-learning recommendation layer, AutoMatch's hard filters, the CodeSignal readiness scores or AI Chat Filtering.

    Have a URL that disputes this?

FRIA Support

2 items27

Data Governance Disclosure

8 items50
  • DocumentationCaptured Sep 25, 2026

    The Trust & Security page claims annual SOC 2 Type II audits, GDPR compliance and AWS hosting with encryption and automatic backups, and directs questions to privacy@ripplematch.com; no report is published.

    https://ripplematch.com/trust-security

  • DocumentationCaptured Sep 25, 2026

    A help article claims SOC 2 Type I and Type II certification and GDPR compliance, with further detail provided only on request.

    https://resources.ripplematch.com/data-security-compliance

  • DocumentationCaptured Sep 25, 2026

    Section 5.6 of the MSA, last updated 12 February 2026, discloses that RippleMatch uses third-party AI providers. It commits that neither RippleMatch nor those providers will train models on customer data, inputs or outputs, or use them for analytics, benchmarking or product development.

    https://app.ripplematch.com/static/pdfs/msa-6.pdf

  • DocumentationCaptured Sep 25, 2026

    RippleMatch says its AI Chat Filtering feature, which turns plain-language requests into candidate filters, sends no personally identifiable information through the AI and makes no hiring decisions.

    https://ripplematch.com/insights/our-latest-ai-innovation-ai-chat-filtering

  • DocumentationCaptured Sep 25, 2026

    The privacy policy effective 16 September 2026 names JobGet, Inc. of Boston as GDPR controller and allows submitted content to be kept indefinitely after an account is closed. Apart from listing an EU right to know about automated decision-making, it says nothing about the matching algorithm or Fit Scores.

    https://app.ripplematch.com/v2/public/privacy

  • DocumentationCaptured Sep 25, 2026

    The candidate help center says deleting an account erases all the data a candidate has shared, which conflicts with the privacy policy's indefinite-retention clause.

    https://resources.ripplematch.com/how-do-i-delete-my-account

  • Public statementCaptured Sep 25, 2026

    JobGet's acquisition release says its playbook is to move acquired businesses onto shared infrastructure after connecting them to JobGet's candidate supply.

    https://www.jobget.com/press/releases/jobget-acquires-ripplematch-expanding-ai-driven-hiring-platform

  • AbsenceCaptured Sep 25, 2026

    No public DPA, subprocessor list, retention schedule, training-data description, ISO 27001/42001 certificate or trust center was found, and nothing public explains how RippleMatch candidate data will be governed within JobGet.

    Have a URL that disputes this?

Human Oversight Design

8 items57

Post-Market Monitoring

4 items37
  • DocumentationCaptured Sep 25, 2026

    An UptimeRobot status page, not linked from the homepage, tracks two HTTP(s) monitors (the production app and the splash page) with 90-day uptime bars. It records only automated outage data, such as a five-minute splash-page outage on 24 September 2026, with no incident write-ups or postmortems.

    https://status.ripplematch.com/

  • Audit reportCaptured Sep 25, 2026

    The BABL summary describes an internal Algorithm Risk Committee, chaired by a software engineer, that owns disparate-impact risk and produced risk assessments in 2022 and 2024; none has been published.

    https://8139278.fs1.hubspotusercontent-na1.net/hubfs/8139278/RippleMatch%20babl%2006.27.2024.pdf

  • DocumentationCaptured Sep 25, 2026

    The only published contact for data protection and security questions is privacy@ripplematch.com.

    https://ripplematch.com/trust-security

  • AbsenceCaptured Sep 25, 2026

    No security.txt was found (ripplematch.com/.well-known/security.txt returns 404), and there is no vulnerability-disclosure policy, model-update changelog or public bias-monitoring dashboard; there has been no bias re-audit since June 2024.

    Have a URL that disputes this?

Customer Documentation

6 items60

Editorial notes

Company overview

RippleMatch was founded in 2016 and is based in New York. It runs an early-career hiring marketplace that draws candidates from more than 1,700 US universities. Its AutoMatch engine emails a role to students who pass the recruiter's hard filters. Applicants are then ranked with a 0-100 Fit Score, built from criteria the recruiter weights, such as school, GPA, major and internships. Newer features add CodeSignal-verified skill badges, a readiness score, AI chat filtering, interview scheduling, a CRM and campus-event tools. RippleMatch raised a $45m Series B led by Goldman Sachs Asset Management in 2022, and Audrey Patenaude became CEO in August 2025. JobGet, which also owns Snagajob, announced the acquisition on 28 May 2026 as its sixth, and said its playbook is to move acquired businesses onto shared infrastructure. Since 16 September 2026 JobGet, Inc. of Boston has issued RippleMatch's privacy policy and terms of service, and the platform became free for universities on 17 September 2026.

Regulatory exposure

RippleMatch had its Fit Score audited as though it were an NYC Local Law 144 automated employment decision tool, and its help center tells customers that RippleMatch takes care of their NYC compliance. But the latest public audit summary is from BABL AI, dated 27 June 2024, which is well outside the law's one-year window. That gap comes as DCWP has promised tougher enforcement after the December 2025 State Comptroller audit. Under the EU AI Act, matching, filtering and ranking candidates is high-risk (Annex III point 4), with the obligations now deferred to 2 December 2027. RippleMatch mostly serves US campus hiring and publishes nothing about the Act beyond a claim of GDPR compliance. In Illinois, HB 3773 has required notice of AI use and barred zip-code proxies since 1 January 2026. Recruiters on RippleMatch can weight school name, prestige and location, SAT/ACT scores and varsity athletics, all of which invite scrutiny as proxies for protected classes. Colorado's SB 26-189 disclosure rules (from 1 January 2027), California's FEHA rules on automated-decision systems (since 1 October 2025, with four-year record retention) and the CPPA's ADMT rules (from 1 January 2027) also cover employers that use its scores and filters. RippleMatch gives no guidance on any of these laws.

Path to a higher score

The biggest gain would come from publishing a current independent LL 144 audit and keeping to the yearly schedule RippleMatch already claims. The audit should also cover the machine-learning recommendation layer, AutoMatch's hard filters, the CodeSignal-based readiness scores and AI Chat Filtering, and should test whether the school-prestige, SAT/ACT and athletics criteria act as proxies for protected classes. RippleMatch should also:

  • make its public statements agree on whether AI evaluates applicants and whether it collects demographic data;
  • publish system documentation and instructions for use;
  • release a public DPA, subprocessor list and retention schedule that match its promise to erase data on account deletion, and explain how candidate data is handled inside JobGet;
  • add deployer guidance for the EU AI Act, Illinois, Colorado and California, with candidate-notice templates;
  • add a security.txt, an incident history and a model-change log to its two-monitor uptime page.

Regulatory frame

What applies to candidate sourcing AI.

Ranking outputs are inside Annex III §4 when they influence hiring decisions. GDPR Article 22 (automated decision-making) and the GDPR rights around profiling apply independently for EU candidates.

Keep reading

All sourcing vendorsHow this score is builtAnnex IV section-by-section: what AI hiring vendors must documentWhat makes a defensible NYC LL 144 bias audit

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Ranking

Others rated in Candidate sourcing AI

Ranked 41 of 86 by weighted total under rubric v1.0. The ordering is arithmetic on the rubric and carries no view on which tool suits a given hiring process.

  1. #38Gloat47F
  2. #39365Talents46F
  3. #40Brainner46F
  4. #41RippleMatchThis profile46F
  5. #42ClearCo (ClearCompany)46F
  6. #43Darwinbox46F
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Conflicts of interest

No vendor pays for placement, scoring, or removal. Casework - the consulting firm that operates this directory - provides paid services to some vendors. Any active or recent (within 24 months) commercial relationship is disclosed on the affected vendor profile and the review is reassigned to an independent reviewer. See the full policy on About.

Casework has no commercial relationship with this vendor.