AI that earns its place in production.

Agents, LLM-powered tools, and AI-native systems — built by engineers who ship.

From Idea to Production

Our process is the eval.

Most teams treat AI like a feature spec. We treat it like an engineering problem with measurable outputs from the first commit.

01

Pressure-test

Is AI actually the right answer? We answer this first, often saying no.

02

Eval-driven design

Test sets and quality bars before code. The eval is the product spec.

03

Iterate to threshold

Build, measure, tune. The bar is shipped quality, not demo magic.

04

Ship + observe

Production with telemetry, fallbacks, and an honest report card.

What we build

Six capabilities. All in production.

Product Engineering

Embedded engineers who own outcomes, not just tasks.

Experience Design

Research-led design that makes every next step obvious.

Applied AI

Agents and automations that improve real work.

Cloud Infrastructure

Cloud built to scale cleanly and stay reliable.

Commerce & Payments

Stripe-certified payment flows that convert and scale.

Case study · Tier-1 Support Agent

tier-one-agent — claude code
01  ERROR DETECTED  NullPointerException in checkout.service:142>  scanning error logs · 3 occurrences in 2h
02  CLAUDE CODE>  reproducing · reading checkout.service · writing fix>  running tests · 14 passed
03  PULL REQUEST OPENED  PR #1284 — fix: guard null cart in checkout>  linked to incident · awaiting review

Closed 80% of tier-1 tickets — quietly.

A B2B SaaS company was drowning in repetitive support tickets. We built an AI agent grounded in their help docs and ticket history, with strict guardrails on what it could promise. It now handles the bulk of tier-1. The team focuses on the cases that need a human.

80%tier-1 resolution
6 wksto first deploy
3.2xteam capacity
Stack
Anthropic ClaudeLangGraphPineconePostgresModal
Read the full case study

How we're different

The honest comparison.

Generic AI Vendor

Demo-driven. "Look what AI can do."

A wrapper around someone else's model.

Locked in to one provider.

RAVN

Eval-driven. "Here's what it does, measured."

Engineering around the model — fallbacks, observability, version control.

Model-agnostic. Right tool for the job, swappable at any layer.

By the numbers

Production, not theater.

30+AI features shipped
12Agents in prod
<2 wksMedian first deploy
85%Features keep eval
4.9★Client satisfaction
StackStackOpenAIAnthropicVercel AILangChainPineconeModalPostgres

Ready when you are

Your next build starts here

Tell us what you’re working on. We’ll tell you how we’d ship it — usually within a single business day.

Built by people, for people.

The team you’ll actually be working with.

US business hours · Nearshore execution · No overnight handoffs