Static analysis + AI for embedded code security across SAST, SCA, and secrets
Semgrep combines deterministic static analysis with large language models (GPT-4, Anthropic, Hugging Face) to detect vulnerabilities, triage risk, and suggest fixes directly in development workflows. The company is actively adopting multiple AI vendors while maintaining OCaml and Rust for its core analysis engine, signaling a shift toward AI-assisted remediation. Sales hiring (15 open roles) outpaces engineering (9), pointing to post-product-market-fit expansion into larger enterprise accounts.
Semgrep is a code security platform that unifies SAST, SCA, and secrets scanning into a single developer-focused tool. The product embeds security checks into CI/CD pipelines and IDEs, catching vulnerabilities before code ships. The platform uses deterministic static analysis paired with AI reasoning to reduce false positives and prioritize reachable risks. Teams across multiple development environments (Python, TypeScript, JavaScript) can define or reuse security rules in a portable format. Customers span mid-market and enterprise (201–500 employees), with sales and customer success operations running on Salesforce and Outreach.
Core analysis: OCaml and Rust. Backend: Python, TypeScript, PostgreSQL, Flask. Infrastructure: Kubernetes, AWS, GCP. Integrations: GitLab, CircleCI, Jenkins, Buildkite. AI: GPT-4, Codex. Observability: Datadog, OpenTelemetry.
United States, Australia, United Kingdom, and Singapore. Most roles are posted in the US market.
Semgrep's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.