Services
What We Build For You
From a single Claude Code install to a fully automated multi-agent workflow, we handle the setup so your team can focus on the work that actually matters. Everything is documented, secure, and handed off with training.
Claude Code Installation & Configuration
Claude Code is Anthropic's AI coding agent — it reads your codebase, writes and edits files, runs commands, and executes multi-step tasks directly in your terminal. Getting it working properly requires more than running an installer. We configure it correctly from the start.
Most teams install Claude Code, open it once, and then run into problems: wrong model
selected, no project context, permissions too broad or too narrow, API costs spiraling
because there's no token budget set. We handle all of that. Every machine gets a
custom CLAUDE.md file that tells the agent who you are, what your codebase
does, and how you want it to behave. That context is the difference between an agent
that needs constant correction and one that works on the first try.
What's included
- Claude Code installed and authenticated on every machine
- API key management and usage limit configuration
- Custom
CLAUDE.mdwritten for your project and team - Model selection tuned to your workload (Sonnet vs Opus vs Haiku)
- Permission scope configured — what the agent can and can't touch
- MCP server baseline (filesystem, search, browser)
- Team walkthrough — 30-minute live session, recorded
- Written runbook for your team
Who this is for
Engineering teams, solo founders, and technical operators who want AI coding assistance that actually fits their workflow. If you've tried Claude Code and it felt clunky or unpredictable, this is the fix.
Development Environment Setup
Running AI agents in production requires a controlled environment. Without one, agents can access things they shouldn't, sessions disappear when your terminal closes, and there's no audit trail. We build the infrastructure that makes agents safe to run continuously.
This is the setup we use ourselves. It's based on Docker sandboxes with iptables firewall rules so the agent can only reach the domains you explicitly whitelist. Sessions live in tmux, which means an agent running a 2-hour task won't die if your laptop goes to sleep. SSH is hardened — key-only authentication, port changed, fail2ban enabled. It's the kind of setup a security-conscious CTO would build, done in a day instead of a week.
What's included
- SSH hardening — key-only auth, non-standard port, fail2ban
- tmux configuration with named sessions and status bar
- Docker sandbox with isolated agent execution environment
- iptables firewall with domain whitelist for agent outbound traffic
- Volume mounts configured — agent reads/writes only what it needs
- Environment variable management (no secrets in code)
- Startup scripts so everything comes back after a reboot
- Basic logging setup for agent activity
Who this is for
Teams running AI agents on production servers, Mac Minis, or cloud VMs that need isolation, persistence, and a clear security boundary. Also useful if you're running automated workflows overnight or on a schedule.
What the stack looks like
Custom Agent & Workflow Building
This is where real leverage comes from. We build AI agents designed around your specific processes — the ones that currently eat hours of manual work every week. Every workflow is custom; we don't sell templates.
We start by understanding what you actually do: which data moves where, what decisions get made manually, what output you need and when. Then we build an agent or workflow that handles it. Examples: a weekly report that pulls from your CRM and project management tool, formats it, and emails it to leadership every Friday morning. An agent that monitors a shared inbox, categorizes requests, creates tickets, and drafts replies. A pipeline that pulls prospect data, enriches it, scores it, and adds qualified leads to your outreach sequence. These aren't hypotheticals — they're the kinds of things we've already built.
What's included
- Discovery session to map your current workflow and pain points
- Custom agent built to your spec, in Python or TypeScript
- MCP server setup to connect the agent to your tools
- Cron job or trigger-based scheduling
- Error handling, retry logic, and failure alerts
- Prompt engineering specific to your use case
- Multi-agent orchestration if your workflow needs parallel steps
- Full source code ownership — no vendor lock-in
- Documentation and handoff session
- 2 weeks of post-launch support included
Who this is for
Businesses with a specific, repeating process that's currently done manually. If someone on your team spends more than 2 hours a week on a task that follows a consistent pattern, it's a candidate for automation.
Tools we connect to
If your tool has an API, we can connect an agent to it. We set this up using MCP (Model Context Protocol) servers, which give the AI direct, scoped access to your tools without requiring custom integration code for every action.
Ongoing Support & Optimization
AI agents drift. The API changes, your process changes, and prompts that worked six months ago stop working well. Ongoing support keeps everything running and improves over time.
This isn't a generic "we'll answer your questions" support package. It's a structured monthly engagement: we review what's running, check error logs, tune prompts, and identify new automation candidates. As your use of AI matures, we expand the system — new agents, new integrations, more complex orchestration. We treat your automation stack like live infrastructure, not a one-time project.
What's included
- Monthly 60-minute review call
- Agent performance monitoring and error log review
- Prompt updates and model version upgrades
- Minor workflow adjustments (up to 4 hours/month)
- Priority access for bug fixes (<24h response)
- Roadmap planning — what to automate next
- New agent development at a reduced rate
Who this is for
Teams that have deployed at least one custom workflow and want it maintained as their processes evolve. Also useful for companies where AI is becoming a core part of operations and they want expert oversight rather than managing it internally.
Clear Pricing, No Surprises
Fixed-scope packages for most teams. Enterprise and complex custom work is quoted after a discovery call.
Get your team up and running with Claude Code, properly configured from day one.
- Claude Code installed on up to 5 machines
- API key setup and spending limits configured
- Custom
CLAUDE.mdfor your project - Model and permission tuning
- Basic MCP server setup (filesystem + search)
- 30-minute team walkthrough, recorded
- Written setup documentation
Full environment plus two custom workflows that save your team real time every week.
- Everything in Starter (up to 10 users)
- Full dev environment setup (Docker + tmux + SSH)
- iptables firewall and domain whitelist
- 2 custom agents or automated workflows
- MCP server setup for your tools
- Cron scheduling and failure alerts
- 2 weeks post-launch support
- Full source code, yours to keep
Multi-team rollout, complex orchestration, and a dedicated partner for your AI infrastructure.
- Everything in Professional (unlimited users)
- Unlimited custom agents and workflows
- Multi-agent orchestration systems
- Multi-team or multi-office rollout
- Dedicated Slack channel with <4h response
- Monthly retainer for ongoing development
- Security review and compliance documentation
- Executive briefings on AI capabilities and roadmap
Prices listed are starting points. Final pricing depends on number of users, infrastructure complexity, and number of workflows. All engagements start with a free 30-minute discovery call.
Common Questions
Straight answers to what people usually ask before booking a call.
Claude Code is what we specialize in, but yes — we can integrate with other AI coding tools and models depending on what your team already uses. The infrastructure work (Docker, SSH, tmux, MCP servers) is largely model-agnostic. If you're using Cursor, Copilot, or running your own models, we can still help with the environment and workflow automation layer. That said, Claude Code's agentic capabilities are meaningfully ahead of most alternatives right now, which is why we focus there.
Claude Code installation is same-day — usually 2–4 hours depending on team size. Dev environment setup (Docker + SSH + firewall) is 1–2 days. Custom workflows take 1–2 weeks each, depending on how many integrations are involved and how much the process needs to be mapped before we can build it. We give you a firm timeline before any work starts.
For Claude Code setup, we need temporary remote access to the machines we're configuring (screen share or SSH). We don't need access to your codebase itself — we're setting up the tool that reads it, not reading it ourselves. For custom workflow builds, we'll need API credentials for the tools we're connecting to. We use read-only credentials where possible and document everything we access. We're happy to sign an NDA before any engagement starts.
Every engagement includes a post-launch support window (2 weeks for Professional, custom for Enterprise). For changes outside that window, you have two options: hire us for a one-off change request (usually a few hundred dollars depending on scope), or sign up for a monthly retainer that covers ongoing updates and maintenance. Since you own the source code, you can also make changes yourself — or have another developer do it. We won't gate you out of your own system.
No. The Starter and Professional packages are one-time, fixed-price engagements — no ongoing commitment. The monthly retainer is month-to-month; cancel any time with 30 days' notice. Enterprise contracts are negotiated individually, but we try to keep terms reasonable. We'd rather earn your business every month than lock you in.
Software companies, agencies, professional services firms, and operations-heavy businesses. The common thread is that you have repeating workflows — report generation, data movement, inbox triage, CRM hygiene, lead processing — that eat time and follow a consistent enough pattern that an agent can handle them. Industry-specific knowledge matters less than process clarity. If you can describe what happens today step by step, we can likely automate most of it.
It starts with a 30-minute call — free, no pitch. We ask about your current tools, which processes are most painful, and what "success" looks like for you. From that we'll tell you honestly whether your situation is a good fit for what we do. If it is, we send a short scope document with a fixed price and timeline before any work starts. No vague estimates, no hourly billing that balloons.
MCP stands for Model Context Protocol — it's an open standard developed by Anthropic that lets AI agents connect directly to external tools and data sources. Think of it as a standardized plugin system. Instead of writing custom code every time you want Claude to interact with ClickUp or your database, you install an MCP server for that tool and the agent can use it natively. It dramatically reduces the amount of glue code needed to connect AI to your existing stack. We set up and configure MCP servers as part of our workflow builds.
Ready to Get Started?
Book a free 30-minute discovery call. We'll look at your current setup, identify where AI agents can save real time, and tell you what it would cost and how long it would take. No commitment required.