Ship Intelligent Systems on Infrastructure That Scales
BugOps pairs agentic AI engineering with battle-tested DevOps. From LLM systems to Kubernetes and Terraform, we architect, automate, and operate platforms built to last.
What We Do
End-to-end engineering across the AI and infrastructure stack — from autonomous agents to the platforms that run them.
Agentic AI Development
Production-grade autonomous agents and LLM workflows — tool use, retrieval, evaluation, and guardrails wired into your existing systems.
LLM & RAG Systems
Retrieval-augmented generation, fine-tuning, and inference pipelines designed for accuracy, observability, and cost control at scale.
Cloud & Platform Engineering
Well-architected platforms on AWS, GCP, and Cloudflare — designed for resilience, security, and developer velocity from day one.
Kubernetes & Containers
Container orchestration done properly — cluster design, GitOps delivery, autoscaling, and the operational guardrails to run it safely.
Infrastructure as Code
Terraform and OpenTofu modules, reproducible environments, and policy-as-code so your infrastructure is reviewable, versioned, and auditable.
CI/CD & Release Automation
Fast, trustworthy delivery pipelines — automated testing, progressive rollouts, and zero-drama deploys that ship on demand.
Tools & Platforms We Work With
How We Work
A pragmatic, repeatable process that turns ambiguous problems into reliable, automated systems.
Assess
We map your systems, constraints, and goals — finding the highest-leverage problems before writing a line of code.
Architect
We design pragmatic, well-bounded systems — choosing battle-tested tools over hype and documenting the trade-offs.
Automate
We codify everything — infrastructure, pipelines, and agentic workflows — so it is reproducible, reviewable, and fast.
Operate
We instrument for observability and hand over runbooks, so your team can own and evolve the platform with confidence.
Let's Build Something Resilient
Whether you're standing up AI capabilities, taming your infrastructure, or both — we'd love to hear what you're working on.