Clearly AI

Name: Clearly AI
Brand: Clearly AI

AI Native

Automate security reviews across the SDLC. Eliminate backlogs and ship secure products faster.

Est 2024|Raised $13.9M|3 Ref Customers

LinkedIn 2K|Web traffic 2K|FTEs 10|HQ Seattle, WA

Published Oct 15, 2026

01Common complaints

1. You primarily need SOC 2/ISO compliance automation and auditor workflows: Vanta or Drata may be better as primary systems of record for compliance evidence collection. 2. Your primary need is inbound customer questionnaires and trust center automation: Conveyor or similar competitors are more directly aligned for that use case. 3. You require EU/UK data residency: the vendor's subprocessor documentation indicates customer data is kept in the United States. 4. You cannot tolerate early-stage vendor risk: limited independent review footprint and an evolving roadmap may be misaligned with conservative procurement. 5. You require a specific, standardized threat modeling artifact format and deep diagramming integrations: validate support for required toolchain conventions during a pilot.

Deal disqualifiers (poor fit)

Needs EU/UK data residency today (vendor materials indicate U.S.-only processing)
Requires immediately verifiable compliance certifications (not evident in vendor materials)
Very small organizations where manual processes are still manageable

Publicly evident limitations / unknowns

Security certifications are not publicly documented.
Pricing is not publicly listed.
Limited independent reviews are available on major platforms.
Data residency is stated as US-only in subprocessor documentation.

Roadmap transparency

No public product roadmap was found in accessible sources.

02Why they buy

Unique selling points that appear supported (requiring buyer validation)

Integration with engineering workflows (Jira and common document systems) to automate aspects of security decision documentation.
Vendor states the product can be customized to internal policies and terminology.
The vendor frames the product as human-in-the-loop, stating that humans make final decisions.

Unique selling points that are vendor-claimed and require verification

Vendor-claimed coverage or acceleration multipliers (e.g., high multiple claims) are not independently verified and should be evaluated in a pilot.
Statements about avoiding incorrect model outputs should be validated with adversarial testing and real artifacts.

Areas where competitors have advantages

Review ecosystem and buyer validation: competitors such as Conveyor, Vanta, and Drata have larger footprints and more publicly available evaluations.
Breadth of compliance program support: Vanta and Drata typically provide broader end-to-end compliance lifecycle capabilities.

03Field reports

Reality check on review availability

Clearly AI is relatively new (founded 2024). As of this research:

No verified G2, TrustRadius, Gartner Peer Insights, or Capterra listing was found for Clearly AI in accessible crawling.
Gartner Peer Insights is often difficult to crawl, and searches did not surface a Clearly AI product page during this research run.

This lack of mainstream review-platform presence is common for early-stage enterprise vendors, but it limits independent validation.

Vendor-published testimonials (positive; not independent)

Clearly AI’s homepage includes quotes attributed to named security/privacy professionals. Examples include: - A Webflow engineering manager commenting on collaboration and accuracy during spec reviews and threat modeling. - A privacy engineer stating the tool identifies privacy-related details more consistently than some internal processes. - A security manager noting that the tool requests additional input when unclear. **Caveat:** These are vendor-selected testimonials and are not a substitute for independent reviews.

Community discussion (mixed/limited; more independent)

A Reddit thread in r/cybersecurity includes a discussion about tools for automated security review and due diligence. In replies: - An account claiming to be the founder of Clearly AI commented on the company being an accelerator-backed startup focused on design reviews and threat modeling using AI. - Other commenters mentioned alternative tools or described building internal agents. **Interpretation:** This is not a systematic product review; it indicates vendor activity in practitioner communities and some level of public engagement.

Common reasons customers choose it (inferred)

Based on case studies and product messaging, likely purchase drivers include:

Reducing cycle time for design reviews and threat modeling
Handling increased review volume without proportionally increasing headcount
Integration with Jira-based intake workflows
Producing consistent, standardized outputs for review processes

Why some customers might leave / not buy (inferred)

Given the lack of independent reviews, the most supportable non-buy factors are category-typical and based on what is not publicly documented:

Security/compliance proof not clearly published (SOC 2/ISO)
Data residency limited to the United States (could be a blocker)
Early-stage vendor risk (support, roadmap volatility)
Preference for a broader GRC suite rather than a specialized point solution

Case Study 1: Rivian (vendor-published)

Clearly AI publishes a customer story describing Rivian’s privacy and AI governance scaling challenge. Claimed outcomes include: - A substantial reduction in review turnaround time - A several-fold increase in review capacity - A multi-month proof of concept **Critical evaluation:** - These metrics are vendor-published and likely based on customer statements; the methodology and baselines are not independently audited. - The operational narrative (review volume growth, Jira-based intake integration) is the most verifiable aspect at a process level. - Buyers should ask for details about the types of reviews included/excluded, error rates, human rework time, and the prior process maturity when evaluating similar claims.

Case Study 2: HID Global (vendor-published)

The vendor describes HID using the platform for threat modeling and preparing for regulatory documentation efforts across a large product portfolio.

Critical evaluation:

The narrative suggests utility for bulk documentation generation and early identification of compliance gaps, but outcome metrics are described qualitatively and lack independent verification.

Additional traction claims (press)

A regional technology outlet reported the product is used by several enterprise customers and listed notable customer logos.

Critical evaluation:

Press reports are a stronger signal than vendor-only pages but often derive customer counts and logos from company statements. Verify logo usage and customer references during procurement.

04Best fit

Company size

Based on the enterprise logos and the problem type:

Likely best fit: mid-market to very large enterprises
Security/privacy teams that are under-resourced relative to engineering throughput

Industries/verticals

Strongest fit where privacy and security reviews are frequent:

Automotive / connected devices
Security/software infrastructure vendors
Fintech
Enterprise SaaS

Roles and personas

Decision makers: Head of Product Security, CISO organization, Head of Privacy/AI Governance, GRC leadership
Champions/users: Product security engineers, security architects, privacy engineers, compliance program managers

Qualification criteria (good fit)

High volume of design reviews and threat models
Standardized intake processes (e.g., common issue-tracking systems)
Internal policies and standards that can be ingested and enforced
Desire to shift security review left without expanding headcount significantly

05The pitch

What the product does (core value proposition)

Clearly AI is an AI-native platform intended to automate and accelerate security, privacy, and compliance reviews that can slow software delivery—particularly design reviews and threat modeling. The vendor describes the product as supporting security and privacy teams, with humans retained as final decision-makers, by: - Ingesting existing artifacts (tickets, docs, policies, specs) - Producing structured assessment outputs (e.g., threat models, risk findings, recommendations) - Integrating into existing workflows (e.g., Jira) On the product site, Clearly AI emphasizes automating repetitive governance, risk, and compliance (GRC) and security review tasks while retaining human oversight.

Target market and market positioning

**Primary audience (inferred from messaging, case stories, and integrations):** - Mid-market to enterprise organizations shipping frequently (high engineering throughput) - Organizations with lean security/privacy teams facing review backlogs - Regulated and compliance-heavy contexts (privacy impact assessments, vendor reviews, EU regulations like CRA) **Positioning:** - Emphasis on reducing cycle time for reviews - A workflow-embedded platform (integrates with common engineering systems) - Positioned to increase the productivity of security engineers rather than to replace them

Get a comprehensive analysis of Clearly AI including market position, competitive landscape, adoption trends, and peer benchmarks.

Download full report →

Published Oct 15, 2026

01Common complaints

You primarily need SOC 2/ISO compliance automation and auditor workflows: Vanta or Drata may be better as primary systems of record for compliance evidence collection.
Your primary need is inbound customer questionnaires and trust center automation: Conveyor or similar competitors are more directly aligned for that use case.
You require EU/UK data residency: the vendor's subprocessor documentation indicates customer data is kept in the United States.
You cannot tolerate early-stage vendor risk: limited independent review footprint and an evolving roadmap may be misaligned with conservative procurement.
You require a specific, standardized threat modeling artifact format and deep diagramming integrations: validate support for required toolchain conventions during a pilot.

Deal disqualifiers (poor fit)

Needs EU/UK data residency today (vendor materials indicate U.S.-only processing)
Requires immediately verifiable compliance certifications (not evident in vendor materials)
Very small organizations where manual processes are still manageable

Publicly evident limitations / unknowns

Security certifications are not publicly documented.
Pricing is not publicly listed.
Limited independent reviews are available on major platforms.
Data residency is stated as US-only in subprocessor documentation.

Roadmap transparency

No public product roadmap was found in accessible sources.

02Why they buy

Unique selling points that appear supported (requiring buyer validation)

Integration with engineering workflows (Jira and common document systems) to automate aspects of security decision documentation.
Vendor states the product can be customized to internal policies and terminology.
The vendor frames the product as human-in-the-loop, stating that humans make final decisions.

Unique selling points that are vendor-claimed and require verification

Vendor-claimed coverage or acceleration multipliers (e.g., high multiple claims) are not independently verified and should be evaluated in a pilot.
Statements about avoiding incorrect model outputs should be validated with adversarial testing and real artifacts.

Areas where competitors have advantages

Review ecosystem and buyer validation: competitors such as Conveyor, Vanta, and Drata have larger footprints and more publicly available evaluations.
Breadth of compliance program support: Vanta and Drata typically provide broader end-to-end compliance lifecycle capabilities.

03Field reports

Reality check on review availability

Clearly AI is relatively new (founded 2024). As of this research:

No verified G2, TrustRadius, Gartner Peer Insights, or Capterra listing was found for Clearly AI in accessible crawling.
Gartner Peer Insights is often difficult to crawl, and searches did not surface a Clearly AI product page during this research run.

This lack of mainstream review-platform presence is common for early-stage enterprise vendors, but it limits independent validation.

Vendor-published testimonials (positive; not independent)

Clearly AI’s homepage includes quotes attributed to named security/privacy professionals. Examples include:

A Webflow engineering manager commenting on collaboration and accuracy during spec reviews and threat modeling.
A privacy engineer stating the tool identifies privacy-related details more consistently than some internal processes.
A security manager noting that the tool requests additional input when unclear.

Caveat: These are vendor-selected testimonials and are not a substitute for independent reviews.

Community discussion (mixed/limited; more independent)

A Reddit thread in r/cybersecurity includes a discussion about tools for automated security review and due diligence. In replies:

An account claiming to be the founder of Clearly AI commented on the company being an accelerator-backed startup focused on design reviews and threat modeling using AI.
Other commenters mentioned alternative tools or described building internal agents.

Interpretation: This is not a systematic product review; it indicates vendor activity in practitioner communities and some level of public engagement.

Common reasons customers choose it (inferred)

Based on case studies and product messaging, likely purchase drivers include:

Reducing cycle time for design reviews and threat modeling
Handling increased review volume without proportionally increasing headcount
Integration with Jira-based intake workflows
Producing consistent, standardized outputs for review processes

Why some customers might leave / not buy (inferred)

Given the lack of independent reviews, the most supportable non-buy factors are category-typical and based on what is not publicly documented:

Security/compliance proof not clearly published (SOC 2/ISO)
Data residency limited to the United States (could be a blocker)
Early-stage vendor risk (support, roadmap volatility)
Preference for a broader GRC suite rather than a specialized point solution

Case Study 1: Rivian (vendor-published)

Clearly AI publishes a customer story describing Rivian’s privacy and AI governance scaling challenge. Claimed outcomes include:

A substantial reduction in review turnaround time
A several-fold increase in review capacity
A multi-month proof of concept

Critical evaluation:

These metrics are vendor-published and likely based on customer statements; the methodology and baselines are not independently audited.
The operational narrative (review volume growth, Jira-based intake integration) is the most verifiable aspect at a process level.
Buyers should ask for details about the types of reviews included/excluded, error rates, human rework time, and the prior process maturity when evaluating similar claims.

Case Study 2: HID Global (vendor-published)

The vendor describes HID using the platform for threat modeling and preparing for regulatory documentation efforts across a large product portfolio.

Critical evaluation:

The narrative suggests utility for bulk documentation generation and early identification of compliance gaps, but outcome metrics are described qualitatively and lack independent verification.

Additional traction claims (press)

A regional technology outlet reported the product is used by several enterprise customers and listed notable customer logos.

Critical evaluation:

Press reports are a stronger signal than vendor-only pages but often derive customer counts and logos from company statements. Verify logo usage and customer references during procurement.

04Best fit

Company size

Based on the enterprise logos and the problem type:

Likely best fit: mid-market to very large enterprises
Security/privacy teams that are under-resourced relative to engineering throughput

Industries/verticals

Strongest fit where privacy and security reviews are frequent:

Automotive / connected devices
Security/software infrastructure vendors
Fintech
Enterprise SaaS

Roles and personas

Decision makers: Head of Product Security, CISO organization, Head of Privacy/AI Governance, GRC leadership
Champions/users: Product security engineers, security architects, privacy engineers, compliance program managers

Qualification criteria (good fit)

High volume of design reviews and threat models
Standardized intake processes (e.g., common issue-tracking systems)
Internal policies and standards that can be ingested and enforced
Desire to shift security review left without expanding headcount significantly

05The pitch

What the product does (core value proposition)

Ingesting existing artifacts (tickets, docs, policies, specs)
Producing structured assessment outputs (e.g., threat models, risk findings, recommendations)
Integrating into existing workflows (e.g., Jira)

On the product site, Clearly AI emphasizes automating repetitive governance, risk, and compliance (GRC) and security review tasks while retaining human oversight.

Target market and market positioning

Primary audience (inferred from messaging, case stories, and integrations):

Mid-market to enterprise organizations shipping frequently (high engineering throughput)
Organizations with lean security/privacy teams facing review backlogs
Regulated and compliance-heavy contexts (privacy impact assessments, vendor reviews, EU regulations like CRA)

Positioning:

Emphasis on reducing cycle time for reviews
A workflow-embedded platform (integrates with common engineering systems)
Positioned to increase the productivity of security engineers rather than to replace them

Get a comprehensive analysis of Clearly AI including market position, competitive landscape, adoption trends, and peer benchmarks.

Download full report →