Capabilities

Deep engineering across AI, platform, quality, and data—delivered with a product mindset.

01

AI Engineering

  • Production LLM applications
  • RAG systems with evaluation-first design
  • Safety and guardrails
  • Monitoring and feedback loops
02

Cloud & Platform

  • Kubernetes and container platforms
  • Secure reference architectures
  • Practical observability
  • Cost discipline
03

Quality Intelligence

  • Risk-based automation
  • CI signal health
  • Real-user flow coverage
  • Release confidence
04

Data & Search

  • Search relevance
  • Vector and hybrid retrieval
  • Data pipelines and governance
  • Trustworthy knowledge systems
Design stance
01

AI should reduce risk—not introduce new ones.

02

Infrastructure should fade into the background—not demand constant attention.

03

Quality becomes an engineering advantage, not a bottleneck.

04

When information is reliable, velocity increases naturally.