Engineers First, Always

We Solve the
Hard Parts

Distributed systems, cloud infrastructure, AI pipelines — built by engineers who care deeply about how things are put together, not just that they ship.

See What We Build
Rust / Go / Python· GCP / AWS / Azure· Artificial Intelligence· SQL / NoSQL· Devops· Infrastructure as Code

We Pick Up Where
Easy Solutions Stop

The problems worth solving rarely fit a template. We dig into the constraints, understand the tradeoffs, and build something that actually holds.

We're a small team of engineers who've spent years getting things wrong before getting them right. That background shapes how we approach every problem — with healthy skepticism, curiosity about failure modes, and a preference for boring, proven solutions over clever ones.

We don't pitch you a technology stack. We ask what breaks first at scale, and design backward from there.

⚙️

Backend & Distributed Systems

High-throughput, low-latency services. Designed for failure, not just the happy path.

☁️

Cloud Infrastructure

Multi-cloud setup that's actually maintainable. Everything as code, deployments you can reason about.

🤖

AI in Production

LLM pipelines that go beyond the demo. Evals, monitoring, iteration — the unsexy work that makes AI reliable.

🗄️

Data Engineering

The right database for the right job. Cassandra, PostgreSQL, MongoDB — chosen for your access patterns, not defaults.

🌐

Web Applications

Frontend to API, built as a coherent system. No handoff mess, no assumptions lost between layers.

🔧

Internal Tooling

The automation that pays for itself in a month. We build the tools teams actually use — because we've needed them too.

Infrastructure That Doesn't Wake You Up at 3am

Good infrastructure is invisible. We design it to stay that way — even as traffic grows and the system evolves.

  • Deployments that don't require a runbook to understand
  • Kubernetes setups you can hand off to another team
  • Infrastructure-as-code from the very first resource
  • Observability built in, not bolted on after the incident
Server infrastructure

AI That Earns Its Place in the Stack

Not everything needs a model. When it does, we build around the failure modes, not around the pitch deck.

  • LLM orchestration designed around real latency budgets
  • RAG that retrieves accurately, not just approximately
  • Agentic workflows with the right guardrails, not just vibes
  • Evaluation loops so you know when it degrades before users do
AI systems

Good Engineering Is a Habit, Not a Sprint

We care about the systems we leave behind — clear, documented, and easy for the next person to reason about. That's not idealism. It's how you build things that actually last.

Work With Us