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Zenity builds a security platform purpose-built for AI agents—covering discovery, posture management, detection, and response across SaaS applications, cloud platforms, and endpoint devices. The tech stack reveals an ML-first approach (Hugging Face, LangChain, PyTorch, RAG, Anthropic) combined with enterprise infrastructure (Kubernetes, Kafka, Apache Spark, OpenSearch), indicating they're building both detection engines and data pipelines to handle agent security at scale. Hiring is sales and engineering-heavy with accelerating velocity, and projects center on runtime protection, vulnerability detection via LLMs, and CI/CD security—reflecting a company moving fast to capture the emerging agentic-AI security category.
Tech Stack 63 technologies
Core StackPython JavaScript LangChain scikit-learn PyTorch RAG Anthropic Kubernetes Helm Terraform TypeScript Java Scala Kotlin Go Kafka Apache Spark Delta Lake Iceberg AWS Workato HubSpot Zapier Vercel bash Hugging Face Transformers OpenSearch Parquet Avro Azure+32 more
What Zenity Is Building
◆Challenges
- Securing ai agents at enterprise scale
- Defending against security threats
- Meeting compliance
- Establishing ai agent security framework
- Reducing internal friction
- Complex enterprise integrations
- Security around agentic ai
- Long procurement cycles
- Protecting fortune 500 customers
- Security gaps in product and cloud
▲Active Projects
- Platform integration
- Technical escalation resolution
- Enterprise account expansion
- Build genai & copilots security solutions
- Design scalable big data pipelines
- Enhancing detection logic for ai agent runtime protection
- Detecting security vulnerabilities using llms
- Application security program development
- Secured ci/cd pipeline implementation
- Autonomous digital employees
Hiring Activity
25 roles · 25 in 30d
Department
Seniority
Company intelligence
