Qwiet AI
Static code analysis tools
Software composition analysis tools
Static application security testing (SAST) software
DevSecOps software
Software bill of materials (SBOM) software
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What is Qwiet AI
Qwiet AI is an application security testing platform focused on finding and prioritizing security issues in source code and open-source dependencies. It is used by development and security teams to integrate security checks into CI/CD workflows and to triage findings based on exploitability and reachability. The product combines static analysis with dependency analysis and supports generating and managing SBOM-related artifacts for software supply chain use cases.
Risk-based finding prioritization
The platform emphasizes prioritization of findings by focusing on whether a vulnerable function is reachable from the application’s code paths. This can reduce time spent investigating issues that are unlikely to be exploitable in a given application context. It is particularly useful for teams dealing with large volumes of SAST and dependency findings across multiple repositories.
CI/CD and DevSecOps fit
Qwiet AI is designed to run in automated pipelines and to support developer workflows where security checks occur during build and pull-request stages. This aligns with DevSecOps practices where teams want consistent policy enforcement across projects. It can help standardize security gates and reporting across engineering teams.
Covers code and dependencies
The product addresses both first-party code issues (SAST) and third-party component risk (SCA) within the same platform. This supports a more unified view of application risk compared with using separate tools for code scanning and dependency scanning. It also supports SBOM-related needs for tracking components and vulnerabilities over time.
Language and framework coverage varies
As with most SAST/SCA platforms, depth of analysis depends on supported languages, build systems, and frameworks. Organizations with polyglot stacks may find uneven rule coverage or differing levels of precision across languages. Validation against the specific tech stack is typically required before standardizing on the tool.
Tuning and workflow setup required
Effective use often requires configuration of repositories, build contexts, policies, and suppression/triage workflows. Teams may need to invest time to calibrate rules, manage false positives, and align severity thresholds with internal risk standards. Without this tuning, results can be noisy or difficult to operationalize.
SBOM expectations may differ
SBOM capabilities across security platforms can vary by supported formats, depth of transitive dependency capture, and how SBOMs are generated from different ecosystems. Some organizations may require specific standards support and governance workflows (for example, signing, attestation, or distribution processes) that are not fully covered out of the box. Buyers typically need to confirm format support and integration with their compliance tooling.
Plan & Pricing
No public pricing tiers or rates are listed on Qwiet AI's official website (qwiet.ai) or linked official docs. Pricing appears to be sales-led and available via direct contact / request a demo.
Seller details
Qwiet AI, Inc.
Private
https://qwiet.ai/
https://x.com/qwietai
https://www.linkedin.com/company/qwiet-ai/
