It can look, not touch
We give the AI a connector that only allows lookups, called a read-only MCP server. It can find an order or a customer. It cannot change anything through it.
Enterprise AI integration
Your AI can’t see your orders, customers or files, so people paste them into a chat by hand. We connect it to the systems where they already live. You choose what it can see and change, and every lookup and change is recorded.
Start with Gnar Discovery and Design, from two weeks and $15,000. You leave with a build plan that has a fixed price on it.
Enterprise AI integration connects an AI model, such as Claude, to the systems your company already runs. U.S.-based senior engineers at The Gnar Company build those connections. Gnar is a Claude Select Services Partner in Anthropic’s Claude Partner Network. Anthropic makes Claude. The systems include your ERP, where orders and stock live, and your CRM, where customer records live. They also include databases, shared files and your own software product. Most connections are small programs called MCP servers. Each lets AI use one system, only in the ways you allow.
What changes
Ask which orders ship this week. AI looks it up in your order system itself. Nobody pastes anything into a chat.
It can read orders but not change prices. Where your system allows it, the AI only sees what the person asking can see.
Who asked, what the AI looked up, and what it changed. Your security team can review the log.
AI models get replaced. Your connections are not tied to one model, so the next one uses the same connectors and rules.
Two ways in
Some systems only need AI to look things up. Others need it to make changes. We decide which with you, one system at a time.
We give the AI a connector that only allows lookups, called a read-only MCP server. It can find an order or a customer. It cannot change anything through it.
AI cannot change a record directly. Every change passes one checkpoint you control, which checks permission first. A person can approve it before it lands.
Proof
Gnar Immerse training, with MCP connectors



How it works
We map your systems, build the connections with the rules in place, then put them live.
We list each system AI needs to reach, what it may see and change, and who signs off. We also flag messy data or access settings that would block it.
We build the connectors with access rules and a request log built in from the first release.
Before launch, your security team gets the access rules and the request log to review. Then your team runs it, or we keep it working on Maintain, our monthly support plan.
Common questions
Still have questions?
Enterprise AI integration connects an AI model to the systems a company already runs, such as its ERP or CRM. The Gnar Company builds those connections, with the limits you choose for each one. The AI then works from your live records, not from copies someone pasted into a chat.
An MCP server is a connector that lets an AI model use one of your systems. It allows only a short list of actions, such as looking up an order. MCP stands for Model Context Protocol, an open standard for connecting AI to software. The Gnar Company builds MCP servers for ERPs, CRMs and internal databases. A server can be read only, so the AI can find records but cannot change them.
Through a connector you control, never by handing the AI a login. At The Gnar Company, the AI reaches your ERP through an MCP server or an API with its own rules. Seeing a record and changing one are separate permissions. Any change goes through one checkpoint with its own checks, not straight into the ERP.
The Gnar Company connects Claude to internal systems through MCP servers and APIs that your company controls. You set the rules one system at a time. Claude gets only the actions each system needs, and reading and changing are granted separately. A log shows what Claude looked up and changed, so your security team can review it.
No. In an AI integration built by The Gnar Company, you set access one system and one action at a time. The AI can be allowed to read orders but not change prices. It can draft a change that a person approves before it lands. Only the systems on the agreed list get connected. Where your system allows it, the AI uses the asking person’s own access.
Yes. The Gnar Company is a Claude Select Services Partner in Anthropic’s Claude Partner Network. It is a custom software firm with U.S.-based senior engineers, who use Claude in their own work. On AI integration projects, Gnar connects Claude to a company’s own systems, such as an ERP or a document store.
No. The connectors are not tied to one AI model. Claude is The Gnar Company’s default, and Gnar is an Anthropic partner. Gnar also builds with Google’s Gemini API and on Amazon’s AWS Bedrock. The build plan from Discovery says which AI fits your systems.
The Gnar Company can build it in your own account with a cloud provider, such as Amazon Web Services (AWS). You own what gets built, and Gnar keeps no ownership of it.
Yes. The Gnar Company adds AI to software that is already running. Gnar connects the AI model to your product’s own data and services. That way it works on real customer accounts, not only in a demo.
It gets replaced, and your connections stay. The Gnar Company keeps the connectors and access rules separate from the model. The next model uses the same connectors and rules.
Your team or ours. The Gnar Company hands the work over documented, with the code in your own account. Your engineers can run it. Or Gnar keeps it running on Maintain, its monthly support plan, from $1,000 a month. Maintain keeps it online, watches it, and gives you support when something goes wrong.
The Gnar Company quotes each project. The price depends on how many systems the AI reaches and what it may change in each. The first step is Gnar Discovery and Design, from two weeks and $15,000. It maps your systems and ends with a build plan that has a fixed price on it.
Often they should. If your own engineers have the capacity and the direction, do it internally. The Gnar Company will say so on the call. This work is for companies with no engineering capacity of their own to point at this. It also fits teams whose engineers are busy with other work.
Start here
Name the systems and what AI should do in each. We map them, set the rules, and give you a build plan with a fixed price on it.
Talk to us about AI integration