Key Takeaways
- Seattle-based Clearly AI, co-founded by husband-wife duo Emily and Joe Choi-Greene, has raised $8.4 million in seed funding led by Basis Set Ventures, with participation from Crosspoint Capital Partners, Argon Ventures, Ritual Capital, and Y Combinator.
- The platform automates enterprise security and privacy reviews – cutting review times by 90%+ for Fortune 500 clients including Rivian, Ericsson, Okta, and Webflow.
- Clearly AI was simultaneously named a Top 10 Finalist for the RSAC 2026 Innovation Sandbox contest, joining the likes of past finalists Wiz, SentinelOne, and Axonius. Each finalist receives a $5M SAFE investment from RSAC.
- Founded in 2024, the company now has 12 employees and has already evaluated thousands of security-critical products spanning autonomous driving features, stablecoin platforms, and IoT badge scanners.
Quick Recap
Clearly AI, a Seattle-based cybersecurity startup automating enterprise security and privacy reviews, officially announced an $8.4 million seed round on February 10, 2026. The round was led by Basis Set Ventures, with backing from Crosspoint Capital Partners, Argon Ventures, Ritual Capital, and Y Combinator.
The announcement came alongside Clearly AI’s recognition as a finalist in the prestigious RSAC 2026 Innovation Sandbox contest, where it will pitch live at the Moscone Center in San Francisco on March 23. CEO Emily Choi-Greene called it “an exciting moment” and described the company’s mission as building “an entirely new product category” for centralized security, privacy, and AI governance reviews.
Alexa Labs to $8.4M Security Bet
Clearly AI was founded on direct operational experience within large scale technology environments. Emily Choi-Greene led security reviews for hundreds of major products at Amazon Alexa, including Alexa AI and Project Kuiper, where manual review processes limited the number of features that could be properly assessed. Alongside co-founder Joe Choi-Greene, she identified structural inefficiencies in traditional application security workflows.
This experience laid the foundation for an $8.4M investment focused on automating enterprise security reviews. The company’s platform ingests comprehensive system context, including design documents, source code, configurations, and internal knowledge, and evaluates them in a manner similar to a human security engineer. It generates threat models, data flow diagrams, and security assessments using the STRIDE framework, while aligning outputs with each organization’s internal security policies.
Reported outcomes demonstrate material efficiency gains, with Rivian reducing review times by 90% and expanding team capacity fourfold, while HID Global accelerated reviews across more than 300 products. Additional enterprise adoption, including firms such as Affirm, Okta, and Webflow, indicates strong traction among large scale organizations.
Competitive Landscape
To contextualize Clearly AI’s positioning, it can be compared with two similarly staged competitors in the AI powered application security segment, ZeroPath and Fig Security. Both companies have also been selected as finalists in the RSAC 2026 Innovation Sandbox, indicating strong early stage validation within the cybersecurity ecosystem.
While all three operate at the intersection of AI and application security, their differentiation lies in product architecture, automation depth, and integration strategy. This comparative perspective helps clarify Clearly AI’s strategic focus and its relative strengths within a competitive and rapidly evolving security landscape.
| Feature / Metric | Clearly AI | ZeroPath | Fig Security |
| Headquarters | Seattle, WA | San Francisco, CA | RSAC 2026 Finalist |
| Funding Raised | $8.4M Seed | ~$7M Seed | Undisclosed |
| Lead Investor | Basis Set Ventures | SurgePoint Capital | N/A |
| YC-Backed | Yes | Yes | N/A |
| Core Focus | End-to-end security & privacy review automation (threat modeling, PIAs, compliance) | AI-native SAST – code vulnerability detection & auto-fix | Security questionnaire & compliance automation |
| Primary Methodology | STRIDE-based threat modeling + org-specific context ingestion | LLM-powered static analysis + deep program analysis | AI-driven security questionnaire responses |
| Enterprise Clients | Rivian, Ericsson, Okta, Webflow, HID Global, Affirm | Aquanow, Commenda, BRX.AI | Early-stage |
| Key Differentiator | Full-context system reasoning (code + docs + policies); 90%+ review time reduction | Business logic flaw detection; 75% fewer false positives vs traditional SAST | Streamlined vendor security assessments |
| Agentic Capabilities | Automated threat models, DFDs, remediation workflows | Auto-fix PRs with one-click patches | Automated questionnaire completion |
Strategic Analysis
Clearly AI wins on breadth of enterprise security workflow automation – it covers the full SDLC from design review to threat modeling to privacy impact assessments, rather than focusing solely on code scanning. ZeroPath, on the other hand, excels in deep code-level vulnerability detection and offers a more developer-centric, SAST-focused toolset with strong false-positive reduction.
For organizations that need a centralized review platform across security, privacy, and AI governance, Clearly AI is the more comprehensive play; for teams focused purely on catching code-level bugs pre-merge, ZeroPath offers more targeted value.
Techno Trenz’s Takeaway
In my experience covering cybersecurity funding, long term winners are not defined by compelling AI demonstrations alone. Sustainable success is typically achieved by companies that address persistent operational bottlenecks faced daily by security teams. Emily Choi Greene’s insight into the security review challenge was developed through direct experience leading hundreds of reviews at Amazon, reflecting a strong founder market alignment that is uncommon in early stage ventures.
This alignment is further supported by the company’s enterprise adoption profile, which includes Rivian, Ericsson, and Okta. These engagements represent production scale implementations rather than pilot programs, indicating meaningful validation within large and complex IT environments. Such deployments at Fortune 500 scale suggest that the solution is addressing a measurable and recurring need within application security workflows.
