TENEX.AI operates an AI-native managed detection and response (MDR) platform staffed by U.S.-based security analysts. The tech stack—Google Chronicle, EDR/SIEM integrations, GCP/AWS, Claude, and LangChain—reveals a company building RAG-backed investigation workflows and autonomous detection layers. Active projects around large-scale LLM productionization and multi-modal agent experimentation signal a shift from rule-based alerting toward AI-driven threat correlation, while the hiring deceleration (13 roles in last 30 days vs. 93 total open) suggests post-launch focus on product hardening over team expansion.
Tech Stack 56 technologies
Core StackGo Python React Next.js TypeScript PostgreSQL MySQL AWS Vue Docker Kubernetes Rust Java RAG LangChain gRPC Tailwind CSS Snowflake BigQuery Redshift Google Chronicle GCP LangGraph REST Google Cloud Security Command Center SIEM EDR CSS Claude Logstash+25 more
AdoptingRetrieval-Augmented Generation Claude
What TENEX.AI Is Building
◆Challenges
- Scaling platform reliability
- Rapid response to incidents
- Increasing adoption
- Scaling platform to petabytes of data
- Ensuring reliability and security
- Reducing customer churn
- Scaling ai systems for billions of events
- Securing customer assets
- Continuous improvement of threat detection capabilities
- Compliance audit readiness
▲Active Projects
- Autonomous detection ai layer
- Soc 1 type ii audit preparation
- Auto-remediation workflows
- Threat intelligence program development
- Custom detection rules and alerts in google security operations
- Transformation pipeline implementation
- Ci/cd pipeline development
- Experiment with retrieval-augmented generation, tool-calling agents, and multi-modal models
- Rag-backed investigation platform
- Productionizing large-scale llms
Hiring Activity
95 roles · 15 in 30d
Department
Seniority
Notable leadership hires: Sales Director
Company intelligence
