iMocha
HireAIScore rates iMocha 56 out of 100 (grade F, Substantial gaps) under rubric v1.0, last reviewed July 17, 2026. iMocha ranks 10 of 82 vendors rated in Assessment AI, against a category average of 46. That score is drawn from 26 evidence items across 7 rubric criteria for iMocha — 21 with a cited source, 5 recording that nothing was located.
Score breakdown
iMocha, 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.
Article 11 Technical Documentation
Weight 20% · category avg 50
68
+13.6
Bias Audit Transparency
Weight 18% · category avg 41
44
+7.9
FRIA Support
Weight 15% · category avg 31
38
+5.7
Data Governance Disclosure
Weight 15% · category avg 53
66
+9.9
Human Oversight Design
Weight 12% · category avg 55
64
+7.7
Post-Market Monitoring
Weight 12% · category avg 38
48
+5.8
Customer Documentation
Weight 8% · category avg 58
66
+5.3
Total weighted score
55.8(rounded to 56 for display)
Category avg is the mean raw score on that criterion across the 82 Assessment AI vendors in scope of this rubric, this one included.
Strongest criterion
Article 11 Technical Documentation
68raw / 100
Contributes 13.6 to the total. 68 against a 50 category average.
Weakest criterion
FRIA Support
38raw / 100
Contributes 5.7 to the total. 38 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 recordEvidence ledger
- Items
- 26
- Documentation
- 19
- Audit report
- 1
- Public statement
- 1
- Absence
- 5
- With a source URL
- 21 of 26
- Source hostnames
- 2
- Fewest items
- 3
- FRIA Support
These figures measure how thoroughly iMocha was reviewed, not how iMocha performed — an absence row, recording that nothing was located, is counted like any other item.
Article 11 Technical Documentation
4 items68
- DocumentationCaptured Jul 17, 2026
A 15-page 'iMocha AI Inference Engine' technical overview for data-privacy and AI-governance teams documents data sources, skills-taxonomy scoring, confidence decay, explainability, and model governance.
https://drive.google.com/file/d/1p-OW1Ms5wXVu36itMtltyDqI4emWFdg7/view
- DocumentationCaptured Jul 17, 2026
A 3-page Ethical & Responsible AI Datasheet sets out six principles (fairness, reliability & safety, privacy & security, inclusiveness, transparency, accountability) aligned to Microsoft's Responsible AI Standard with an explicit explainability statement.
https://drive.google.com/file/d/15joWpLoiHdz0ViuHwwuOH3LYmVp9FPMe/view
- DocumentationCaptured Jul 17, 2026
The public Trust Center hosts a dedicated 'Responsible AI & Governance' section publishing both AI documents alongside its security and compliance packs.
- AbsenceCaptured Jul 17, 2026
No ISO 42001 certification, model card, or formal EU AI Act Article 11 / Annex IV technical documentation is published.
Bias Audit Transparency
4 items44
- DocumentationCaptured Jul 17, 2026
The AI Inference Engine doc details a scheduled internal bias-monitoring program covering gender, language/accent, recency, and credential bias with methods and quarterly-to-annual frequencies.
https://drive.google.com/file/d/1p-OW1Ms5wXVu36itMtltyDqI4emWFdg7/view
- DocumentationCaptured Jul 17, 2026
iMocha states enterprise customers can request bias-audit reports and that 'annual third-party AI model audits' are conducted, but summaries are available only on written request (gated, not public).
https://drive.google.com/file/d/1p-OW1Ms5wXVu36itMtltyDqI4emWFdg7/view
- Public statementCaptured Jul 17, 2026
The Ethical & Responsible AI Datasheet self-declares bias mitigation across 14 factors including gender, age, race/ethnicity, disability, and career breaks, but this is a self-assessment rather than an independent audit.
https://drive.google.com/file/d/15joWpLoiHdz0ViuHwwuOH3LYmVp9FPMe/view
- AbsenceCaptured Jul 17, 2026
No independent, publicly downloadable NYC LL 144-style bias audit by a named auditor (e.g., BABL AI, DCI, ORCAA, Warden AI) was found on iMocha's site or in web searches.
FRIA Support
3 items38
- DocumentationCaptured Jul 17, 2026
The AI Inference Engine doc is written 'for data privacy officers, AI governance teams, legal counsel, and security reviewers evaluating iMocha for enterprise deployment' and includes a governance Q&A plus a disclaimer that customers remain contractually responsible for employment decisions.
https://drive.google.com/file/d/1p-OW1Ms5wXVu36itMtltyDqI4emWFdg7/view
- DocumentationCaptured Jul 17, 2026
The GDPR page describes iMocha's data-processor role and EU-specific data transfer and processing agreements, and it offers a DPA on request, providing partial deployer-facing contractual support.
- AbsenceCaptured Jul 17, 2026
No EU AI Act Article 27 Fundamental Rights Impact Assessment template or explicit deployer-obligation guidance is published.
Data Governance Disclosure
4 items66
- Audit reportCaptured Jul 17, 2026
The Trust Center publishes ISO 27001:2022 certification and a SOC 2 Type II compliance report (both last updated October 2025), alongside CCPA and Data Privacy Framework badges.
- DocumentationCaptured Jul 17, 2026
The AI Inference Engine doc provides a per-data-element retention table and states models are trained on aggregate anonymized signals with PII removed, individual employee data never used to train shared models, and models static during inference.
https://drive.google.com/file/d/1p-OW1Ms5wXVu36itMtltyDqI4emWFdg7/view
- DocumentationCaptured Jul 17, 2026
The GDPR page describes data-processor status, SCC/Article 46 cross-border transfers, Article 30 audit logs, 24-hour breach notification, configurable retention/deletion, and a dedicated Data Protection Officer.
- DocumentationCaptured Jul 17, 2026
The security guidelines page discloses Azure hosting (East US primary, Northern Europe replica), Cloudflare DDoS protection, AES-256 at rest, TLS 1.2+ in transit, and role-based access control.
Human Oversight Design
3 items64
- DocumentationCaptured Jul 17, 2026
The AI Inference Engine doc positions outputs as advisory decision-support and lists human-oversight mechanisms: manager review/endorse/flag, HR override with documented rationale, employee-initiated disputes routed to a human review process, and retained audit logs.
https://drive.google.com/file/d/1p-OW1Ms5wXVu36itMtltyDqI4emWFdg7/view
- DocumentationCaptured Jul 17, 2026
Explainability is delivered per inference in-product (source contribution weights, raw confidence per source, taxonomy path, recency-adjusted score, validation status), with employees able to view and contest each inferred skill and 'no black-box scoring'.
https://drive.google.com/file/d/1p-OW1Ms5wXVu36itMtltyDqI4emWFdg7/view
- DocumentationCaptured Jul 17, 2026
The Tara AI-interviewer product page frames the tool as supporting fairer human hiring decisions with explainable, structured scoring rather than autonomous decisions.
Post-Market Monitoring
4 items48
- DocumentationCaptured Jul 17, 2026
The AI Inference Engine doc commits to model versioning with pre-update customer notification, 12-month version retention with rollback, 30-day change-management notice, annual third-party AI-model audits, and an AI incident-response process with a customer-notification SLA.
https://drive.google.com/file/d/1p-OW1Ms5wXVu36itMtltyDqI4emWFdg7/view
- DocumentationCaptured Jul 17, 2026
Bias monitoring runs on a defined cadence (quarterly, semi-annual, and annual) across multiple bias types, indicating ongoing production monitoring.
https://drive.google.com/file/d/1p-OW1Ms5wXVu36itMtltyDqI4emWFdg7/view
- DocumentationCaptured Jul 17, 2026
The Trust Center publishes a Security Incident Response Plan and Vulnerability & Patch Management Policy, and states the platform undergoes annual penetration testing.
- AbsenceCaptured Jul 17, 2026
No public status/uptime dashboard, public model-update changelog, or dedicated security.txt/incident channel was found; the only listed contacts are general contact@ and support@imocha.io.
Customer Documentation
4 items66
- DocumentationCaptured Jul 17, 2026
A comprehensive public Trust Center organizes security policies, ISO 27001/SOC 2 certifications, privacy documentation, and AI-governance datasheets in one ungated hub.
- DocumentationCaptured Jul 17, 2026
iMocha maintains full public product pages (e.g., the Tara AI interviewer, skills assessment, and talent-management pages) plus resource hubs and pricing pages.
- DocumentationCaptured Jul 17, 2026
A dedicated GDPR page documents data-subject rights, processing agreements, and a DPA available on request for deployers.
- AbsenceCaptured Jul 17, 2026
No NYC Local Law 144-specific or EU AI Act-specific deployer/compliance guidance is published.
Editorial notes
Company overview
iMocha, founded in 2015 and operated from Pune, India (through the ISO-certified entity Tecknack Technologies Pvt. Ltd., with a US Delaware corporate presence and a California sales line), is an AI-powered skills assessment and skills-intelligence platform. It reports 300+ customer organizations including 15 Fortune 500 companies and raised a $14M Series A in 2022. The product spans pre-hire skills assessments, the AI-LogicBox coding simulator, one-way and conversational AI video interviews via its 'Tara' interviewer, and a skills-taxonomy/intelligence cloud used across hiring, internal mobility, and workforce planning.
Regulatory exposure
Because it scores and ranks candidates, iMocha functions as an automated employment decision tool with exposure to NYC Local Law 144 bias-audit obligations, EEOC adverse-impact standards, Illinois and Colorado AI-hiring rules, and - as an Annex III employment use case - the EU AI Act's high-risk regime. iMocha frames its outputs as advisory decision-support subject to human oversight and states its AI Interview uses NLP on spoken/written responses only (no biometric or facial analysis). However, it publishes no independent third-party bias audit and no EU AI Act FRIA or explicit deployer-obligation guidance; bias-audit and annual third-party AI-model-audit summaries are offered only on written request rather than being publicly downloadable.
Path to a higher score
To raise its score, iMocha should commission and publicly post an ungated independent bias audit (NYC LL 144-style) by a named auditor such as BABL AI, DCI, or Warden AI; pursue ISO 42001 certification and formal EU AI Act Article 11 / Annex IV technical documentation with instructions-for-use; publish explicit EU AI Act deployer and Fundamental Rights Impact Assessment guidance; ungate its third-party AI-model-audit and per-customer bias-audit summaries; and stand up a public status page and model-update changelog for continuous post-market monitoring.
Regulatory frame
What applies to assessment AI.
Assessment is the most-regulated surface in AI hiring. NYC LL 144, EEOC and OFCCP frameworks, Illinois HB 3773, and EU AI Act Annex III §4 all apply, with overlap on bias-audit obligations.
Compare
iMocha against its nearest-scoring peers.
The closest scores in Assessment AI, side by side.
- Side-by-sideiMocha vs Harver56F
- Side-by-sideiMocha vs Sapia.ai56F
- Side-by-sideiMocha vs Cornerstone OnDemand56F
- Side-by-sideiMocha vs Pymetrics (Harver Games)56F
Ranking
Others rated in Assessment AI
Ranked 10 of 82 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.
- #7Harver56F
- #8Sapia.ai56F
- #9Cornerstone OnDemand56F
- #10iMochaThis profile56F
- #11Pymetrics (Harver Games)56F
- #12HackerRank55F
Conflicts of interest
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Casework has no commercial relationship with this vendor.