K
Kai Tech Stack
Agentic AI platform automating enterprise security workflows at machine speed
Kai builds an agentic AI security platform using vLLM, Triton, Ray, and vector databases (Milvus, Pinecone, Weaviate) to replace fragmented human-speed security workflows. The tech stack reveals a company prioritizing LLM inference optimization and real-time ML—vLLM and Triton are inference engines, Ray handles distributed compute, and the vector DB mix suggests heavy embedding-based reasoning. Hiring velocity is accelerating across engineering (7 roles), sales (6), and data (3), with two-thirds of open positions at senior or manager level, indicating a push to scale AI-driven product and go-to-market simultaneously.
Tech Stack 37 technologies
Core StackReact TypeScript GraphQL Next.js Salesforce HubSpot ZoomInfo Python Pandas Tableau Go Java C++ Apache Spark Delta Lake Docker Kubernetes Pinecone Weaviate Databricks Azure Data Factory AWS vLLM Triton Ray Cognism Plotly SQL Milvus Azure Data Lake Storage+7 more
What Kai Is Building
◆Challenges
- Fragmented workflows
- Rebuilding cybersecurity from first principles
- Human speed bottlenecks
- Security silos
- Improving platform reliability
- Messy data
- Data cleanliness and governance
- Lead routing optimization
- Threat detection accuracy
- Real-time security ai reliability
▲Active Projects
- Scalable data platforms and pipelines
- Ci/cd pipelines for data engineering code
- Apache spark clusters and workloads
- Ai infrastructure stack deployment
- Llm productionization
- Dashboard and data model development
- Financial reporting processes
- Real-time intelligence
- Forecasting and strategic planning
- Security analytics platform
Hiring Activity
30 roles · 30 in 30d
Department
Seniority
Company intelligence
