EasyKnock vs Armilla AI

Side-by-side comparison of AI visibility scores, market position, and capabilities

Armilla AI leads in AI visibility (37 vs 30)
EasyKnock logo

EasyKnock

EmergingReal Estate & Property Tech

General

NYC residential sale-leaseback fintech permanently closed December 2024; $127M raised ($28M Northwestern Mutual Series D Feb 2024) before state AG enforcement actions in Michigan/Massachusetts and consumer lawsuits across 5 states led to closure.

AI VisibilityBeta
Overall Score
D30
Category Rank
#649 of 1158
AI Consensus
73%
Trend
up
Per Platform
ChatGPT
24
Perplexity
32
Gemini
32

About

EasyKnock was a New York City-based residential sale-leaseback fintech company — having raised $127 million in total venture funding over 9 rounds including a $28 million Series D led by Northwestern Mutual in February 2024 — that permanently closed in December 2024 following regulatory enforcement actions and consumer litigation. Founded in 2016 by CEO Jarred Kessler and Ben Black, EasyKnock pioneered the residential sale-leaseback model in the United States, allowing homeowners to sell their property to EasyKnock for immediate liquidity while remaining as tenants in their home — targeting homeowners seeking to access equity without moving, those facing potential foreclosure, or property owners seeking capital for investments.

Full profile
Armilla AI logo

Armilla AI

EmergingInsurance Tech

General

AI quality assurance with insurance-backed warranties from Swiss Re and Greenlight Re; EU AI Act compliance assessments backed by YC and reinsurance partners for high-risk AI deployments.

AI VisibilityBeta
Overall Score
D37
Category Rank
#211 of 1158
AI Consensus
57%
Trend
up
Per Platform
ChatGPT
42
Perplexity
44
Gemini
36

About

Armilla AI is a third-party AI quality assurance and warranty company that evaluates AI models for organizations deploying AI in regulated or high-stakes contexts — assessing models against EU AI Act and NIST AI Risk Management Framework requirements for risks including bias, hallucination, robustness failures, and adversarial vulnerabilities, then providing performance guarantees backed by insurance coverage from reinsurers Swiss Re, Greenlight Re, and Chaucer. Founded in Toronto, Canada, Armilla raised $6.81 million total including a C$4.5 million seed round in February 2024 from Mistral Venture Partners, MS&AD Ventures, Y Combinator, and its reinsurance partners.\n\nArmilla's model is unique in the AI governance market — rather than just providing compliance reports, Armilla backs its assessments with insurance warranty products. An enterprise deploying a third-party AI model can purchase an Armilla warranty that pays out if the model performs differently than assessed (fails on bias, accuracy, or robustness metrics), transferring AI performance risk to insurance markets that can price and distribute it. This insurance mechanism creates financial accountability for AI quality claims that audit reports alone don't provide.\n\nIn 2025, Armilla competes in the AI governance, risk, and compliance market with Credo AI, Arthur AI, and AI audit firms for enterprise AI risk assessment and compliance tools. The EU AI Act, fully applicable by August 2025 for high-risk AI systems, is driving enterprise compliance urgency — companies deploying AI in hiring, credit scoring, healthcare, and other regulated contexts need third-party conformity assessments. Armilla's insurance-backed warranty differentiates its offering from pure advisory competitors. The reinsurer backing (Swiss Re, Greenlight Re, Chaucer) provides both capital credibility and distribution through insurance broker channels. The 2025 strategy focuses on growing EU AI Act compliance assessments and expanding the warranty product coverage to more AI deployment use cases.

Full profile

AI Visibility Head-to-Head

30
Overall Score
37
#649
Category Rank
#211
73
AI Consensus
57
up
Trend
up
24
ChatGPT
42
32
Perplexity
44
32
Gemini
36
30
Claude
45
23
Grok
28

Key Details

Category
General
General
Tier
Emerging
Emerging
Entity Type
brand
brand

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