Company profile · 3 min read
Clearly AI: repeatable security, privacy and risk reviews
Clearly AI organizes evidence, review templates, risk triage and approvals for enterprise security, privacy, third-party risk and AI governance teams.
Cofounder of Lazyweb (a16z Speedrun). Previously grew subscriptions and built native ads at Duolingo. Writes First1000 (90,000+ subscribers).
Published · Updated
Clearly AI is trying to turn security and privacy review into a repeatable operating system.
What it does
The current Clearly AI homepage describes reviews across product security, privacy, third-party risk and AI governance. The docs break the product into Projects, sources, Review Templates, Reviews, Knowledge Base, Chat, integrations and a risk registry. A team uploads documents, code, tickets or policies, starts a review, then tracks missing information, approvals and remediation.
That is a better product shape than a chatbot answering a security question in isolation. The output is supposed to remain connected to the evidence and the approval trail.
Why I’d look closer
Clearly AI’s customer story for Ericsson says review times fell by up to 80%, with 85% of vendor assessments auto-completed and more than 300 assessments annually. Those are company-published case-study claims, not independent measurements. The useful underlying idea is more durable: regulated teams can version review templates, keep a knowledge base, route decisions and preserve the source material behind an answer.
The company’s about page says its founders saw the problem while reviewing critical applications at Amazon. It frames the product around making the secure path easier without removing human judgment. That is the right boundary for this category.
What I’d ask
I would ask how a review template is versioned, how missing evidence is surfaced, who can approve risk acceptance, how connected sources are permissioned and what happens when an answer conflicts with policy. The docs expose API and CLI paths, which matters if security review is part of a deployment pipeline rather than a quarterly spreadsheet.
My editorial take
Shortlist Clearly AI if your security, privacy or GRC team repeats the same review work across products and vendors. It is less useful if the organization has no review templates or evidence owners yet. The product’s leverage comes from turning judgment into a repeatable process, not pretending the process can run without people.
Quick facts
| Field | Sourced detail |
|---|---|
| Product | Security, privacy, third-party risk and AI-governance review platform |
| Buyer | Regulated enterprise security, privacy and GRC teams |
| Workflow | Sources → template → review → triage → risk registry → approval |
| Pricing | Not published in the checked pages |
| Main question | Who owns the evidence and the final risk decision? |
Sources checked
| Source | Checked |
|---|---|
| YC company profile | 2026-09-19 |
| Clearly AI homepage | 2026-09-19 |
| Clearly AI documentation | 2026-09-19 |
| Clearly AI about | 2026-09-19 |
Cohort context
Clearly AI is listed in Summer 2024. In our 2026-09-18 directory snapshot, 161 of 248 listed companies in that cohort have YC’s primary industry label B2B (64.9%). This is a current-directory comparison, not an original intake count or a performance ranking. Nine-cohort dataset.
Public website snapshot
Observed 2026-09-19T16:16:55.445Z in raw homepage HTML. This records visible metadata and advertised links, not agent execution or product quality.
| Signal | Homepage observation |
|---|---|
| Product description metadata | Observed |
| Canonical link | Observed |
| H1 or H2 heading | Observed |
| Typed structured data | Not observed in this response |
| Docs/developer link | Observed |
| Pricing link | Not observed in this response |
| llms.txt link | Not observed in this response |
| Markdown alternate | Not observed in this response |
Public observations · Collection method. Missing links here do not establish that a capability or file is absent elsewhere.
About the author
Cofounder of Lazyweb (a16z Speedrun). Previously grew subscriptions and built native ads at Duolingo. Writes First1000 (90,000+ subscribers).
I cofound Lazyweb and publish Mudpie. This is an owner-written publication, not an independent testing organization. Research notes distinguish observations, sourced reporting and editorial judgment.
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