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Custom AI agents & automation

AI agents that answer customers, qualify leads and take routine work off your team, wired into your own systems.

AI agent & training pricing

Simple hourly pricing for agent development and training, or a fixed quote for a clearly scoped build. Either way, you know what you're paying for before we start.

Hourly

For agent development, integrations, and training sessions billed as you go.

$75/hrDevelopment, integration & training
  • Billed in clear, itemized increments
  • No minimum monthly commitment
  • Direct access to the engineer building or teaching
  • Pause or scale up anytime
Most common

Project-Based

For a defined agent build or a training curriculum with a clear scope.

Custom quoteScoped after a free technical audit.
  • Fixed price, agreed before work starts
  • Milestone-based delivery
  • Free technical audit and estimate
  • Source code, prompts, and docs included

No hidden fees

The rate you agree to is the rate you pay.

Real engineers

You talk directly to the people building and teaching.

Your prompts, your rights

You own every agent, prompt, and doc we build for you.

Built to last

Documented, maintainable, and easy for your team to extend.

Not sure whether you need an agent, training, or both? Tell us what you're trying to do and we'll recommend a starting point.

What's included

Use-case scoping

We pin down exactly what the agent should and should not do, and what "good" looks like.

We pin down exactly what the agent should handle, what it should hand off to a human, and what 'good' looks like in practice, before any building starts. That scope becomes the spec everyone builds against, not a moving target.

We look at your actual support tickets, sales conversations, or internal requests, not a guess at what customers might ask, so the agent is built around real demand from day one.

You get a written scope before any building starts: what the agent owns, what it escalates, and what success looks like, so there's no ambiguity about what you're getting.

Common questions

How is this different from a normal chatbot?

A scripted chatbot follows a decision tree. An AI agent reasons over your actual content and can take actions in your systems, and we build in guardrails so it stays reliable.

Which AI models do you use?

We pick the model per use case, usually a current frontier model for quality, with cost and latency in mind. You are not locked to one vendor.

Will it make things up?

We ground the agent in your content and constrain it to that, with a clear "I do not know" path. The Helpy assistant on this site is one we built this way.

Where does our data go?

Into the integrations you approve, nowhere else. We are explicit about what the agent can read and do.

Do you train non-technical people too?

Yes. We tailor sessions to the room, from a plain-English introduction for a non-technical team to hands-on building for developers. No prior AI experience is assumed unless you tell us otherwise.

What's MCP, and why does it matter?

Model Context Protocol is the emerging standard for connecting AI agents to real tools and data sources, instead of a one-off custom integration for every system. We cover it in our technical training and use it in the agents we build.

Can we run models locally instead of a cloud API?

Yes, where it makes sense. Running a model locally trades some capability for full data privacy, no per-token cost, and offline use. We help you decide when that trade is worth it, and set it up.

How does the $75/hr rate work?

It's straightforward, itemized hourly billing for agent development, integration, and training, with no minimum monthly commitment. For a clearly scoped build or curriculum, we'll usually quote a fixed price instead, so you know the total before we start either way.

Why teams switch

AI Agents, Without and With CodeMutual

Without UsWith CodeMutual
Getting startedMonths spent evaluating tools before anything actually shipsA working agent handling real conversations within weeks
AccuracyA generic chatbot that confidently makes things upAnswers grounded in your own content, with a clear "I don't know" path
Your systemsA bolt-on widget that can't see your actual dataWired into your systems through real integrations and MCP
Your teamNobody in-house understands how it actually worksHands-on training so your team can run and extend it themselves
Data privacyUnclear where your data goes or who can see itExplicit about every integration, with local-model options available
Ongoing improvementLaunched once and never touched againTuned on real conversations, with monitoring built in from day one
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