AI automation for Rails teams

Make AI actually work for your Rails team

AI is changing how software gets built — but your team needs the right foundation to benefit. Standardized AI workflows, infrastructure that keeps pace with AI-speed development, and observability to measure the impact. We help you get there.

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Most Rails teams we talk to are hitting the same walls.

The problem

  • ✕  Engineers adopting AI tools ad hoc — no standardized workflows, no sandboxed environments for autonomous coding, no way to run longer tasks without babysitting
  • ✕  AI writes code fast, but slow pipelines erase the benefit — builds drag, test suites flake, deploys bottleneck
  • ✕  No data on how AI is actually affecting throughput or stability — the team can't optimize what they can't measure, and has no way to demonstrate the value they're delivering

The fix

  • →  Standardized Claude Code workflows, sandboxed Docker/devcontainer environments, and a CLI for background agents — so the whole team uses AI consistently and autonomously
  • →  Faster builds, stabilized test suites, and smoother deploys — so infrastructure keeps pace with AI-speed development
  • →  Datadog for pipeline and application health monitoring, plus DORA metrics to establish baselines — so the team can prove the impact of every improvement they make
Services

The foundation your Rails team needs for the AI era

Every engagement is custom, but most Rails teams need help in one of these areas.

🤖

Standardized AI Workflows

Creating a consistent way for the whole team to use AI-assisted development, rather than everyone doing something different.

📦

Sandboxed Dev Environments

Docker and devcontainer setup where AI agents can safely run code, execute tests, and access the browser. Full autonomy without risk to the local machine.

Background Agents

A straightforward CLI for developers to kick off longer-running AI tasks and keep moving, without changing their existing workflow.

CI/CD That Keeps Pace

AI writes code fast, but slow pipelines erase the benefit. Speeding up builds, stabilizing test suites, and smoothing out deploys.

📊

Observability with Datadog

Pipeline and application health monitoring so decisions are based on data, not gut feel.

🚀

DORA Metrics

Instrumenting deployment frequency, lead time, change failure rate, and MTTR. Establishing baselines so the team can see AI's true effect on shipping speed and stability — and demonstrate that story with data.

Why us

Faster than hiring. More focused than doing it yourself.

Building an internal DevEx team takes months. We deliver measurable results in weeks.

Speed

Delivering in weeks, not the months it takes to hire, onboard, and ramp a specialized engineer. Your team gets value while the backlog is still fresh.

🎯

Focus

Deep specialization in Rails developer experience — AI tooling, CI/CD, observability, and DORA metrics. This is all we do, every day, across multiple Rails codebases.

🔑

Ownership

Everything we build lives in your codebase and your team maintains it. No vendor lock-in, no proprietary platform — just tooling your team owns.

Process

How we work together

Start with a focused 2-week assessment — no long-term commitment required. Everything we deliver is work your team owns from day one.

01

Discover

We identify the highest-leverage bottlenecks across your CI pipeline, test suite, deploy process, code review, and AI-assisted coding setup — then deliver a prioritized roadmap your team keeps regardless of next steps.

02

Measure

We instrument your pipeline with DORA metrics to establish baselines — so every improvement we make has a clear before-and-after.

03

Build & Integrate

We build the automations and integrations directly into your Rails stack. No rip-and-replace — your team is empowered to own, maintain, and extend everything we deliver.

04

Iterate

We review the metrics together, tune what's working, and adjust what's not.

Deliverables

What you get

Every engagement produces concrete, actionable deliverables your team owns.

🤖

Standardized AI Playbook

Documented Claude Code workflows, CLAUDE.md configurations, and team-wide standards your engineers use from day one.

📦

Sandboxed Dev Environments

Docker and devcontainer configs so AI agents run safely — committed to your repo, ready to use.

Background Agent CLI Setup

A working async agent workflow your developers can use to kick off AI tasks and keep moving.

Optimized CI/CD Pipelines

Faster builds, reliable test suites, and smoother deploys — shipped directly into your codebase.

📊

Datadog Dashboards

Pipeline and application health monitoring wired into your existing stack.

📋

DORA Metrics Baselines

Live visibility into deployment frequency, lead time, change failure rate, and MTTR — with clear before-and-after for every improvement.

Ready to set your Rails team up for the AI era?

Let's talk about where AI and automation can measurably improve your Rails development workflow.

No commitment required. 30 minutes to see if we're a fit.

Book a Free Discovery Call