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Custom AI agents

AI agent development

We build AI agents for mid-sized companies on NetSuite or a similar system. The agents do routine finance and operations jobs, like matching bank lines at month-end. You choose which changes need a person’s OK, and you own the code. If an agent shouldn’t do the job, we’ll tell you.

Start with a discovery sprint that ends in a guaranteed price, whether or not you build with us.

The requestNew requestReconcile the bank accountNewBank statementAttachedPart ofMonth-end closeThe agentAgent · workingRead the requestRequest and statementDecide the stepsMatch each lineWork in your systemsUpdate the ledgerUnclear itemsSent to a personFinish taskYour systemsWhere the agent does the workNetSuiteInboxFile sharesExcelTask doneUpdateThe requestNew requestReconcile the bank accountNewBank statementAttachedPart ofMonth-end closeThe agentAgent · workingRead the requestRequest and statementDecide the stepsMatch each lineWork in your systemsUpdate the ledgerUnclear itemsSent to a personFinish taskYour systemsWhere the agent does the workNetSuiteInboxTask doneUpdate

AI agent development means building software that does a job your team does by hand today. At The Gnar Company, senior U.S. engineers build each agent. Anthropic, the company that makes the Claude AI model, has vetted us to build with it. We test each agent on your own past cases first, so you see it work before it touches live records.

Fixed milestone price

Any overage on us

Guaranteed outcome

The software works as specified or we fix it

Twelve‑month bug‑free warranty

Three commitments on every build engagement

What changes

Agents do the routine work. You decide what needs a person.

Bank reconciliation · one agentReadMatchUpdateDoneNo copying between screens
Bank reconciliationReadMatchUpdateDoneNo copying between screens

One job, start to finish

It’s month-end. Someone is matching bank lines to the books by hand, one at a time, while the close waits. An agent matches the lines and updates the books. Your team handles only the lines it can’t match.

AgentBank reconciliationBank statementReadLedger entryUpdatedYour systemsConnections builtNetSuiteConnectedInboxConnectedFile sharesConnectedSync
AgentBank statementReadLedger entryUpdatedYour systemsConnections builtNetSuiteConnectedInboxConnectedSync

Inside the systems you run

It works in NetSuite or your other ERP, your inbox and your shared files. We build the connections it needs. An agent is only as good as what it reads. So the discovery sprint checks those records first, and says what needs fixing and who fixes it.

Bank line matchedDoneJournal entryNeeds approvalUnclear chargeTo a person
Bank line matchedDoneJournal entryNeeds approvalUnclear chargeTo a person

Sign-off stays with you

You choose what the agent can touch and which changes need a person’s OK. Every action it takes in your systems is logged, so you can check what it did.

Tests · before it goes liveLast month’s statementsPassedDuplicate and odd chargesPassedAfter an AI model updateRun again
TestsPast statementsPassedDuplicatesPassedModel updateRun again

Tested before it goes live

We test every agent on your own past cases, including the odd ones. Each time we change it, the tests run again. So if its scores drop, we see it before the change goes live.

Two ways in

Start from a job, or from a prototype.

Some teams bring a job they want off their plate. Others bring an AI tool that works in a demo but not yet in daily work.

Job

Start from the job

We look at how the job gets done today and pick the steps an agent can do. Then we build an agent for those steps, inside your systems.

The job, mappedRead the requestAgentLook up the recordsAgentUpdate the ledgerAgentApprove the exceptionsPersonMapped before anything is built
The job, mappedRead the requestAgentLook up the recordsAgentUpdate the ledgerAgentApprove the exceptionsPersonMapped before anything is built
Prototype

Start from your prototype

The prototype works. Getting it into production is a different job, and it is the one we do. Have several? We get the first one into daily use and teach your team to do the rest.

Your prototypeSample dataWorks in a demoIn daily useYour systemsConnectedTestsPassingUnclear casesTo a person
Your prototypeSample dataWorks in a demoIn daily useYour systemsConnectedTestsPassingUnclear casesTo a person

How it works

How we’d work with you

We pick one job with you and build an agent for it. Then we run it, or your team does.

The job todayWhat the agent reads, where it worksRequestsRecordsSystems
The job todayWhat the agent readsRequestsRecordsSystems
Step 1 · Discovery sprint

Map the job

We map the job step by step: what the agent reads and which systems it works in. This is the discovery sprint. It ends with a guaranteed price for each stage of the build, whether or not you build with us.

ConnectionsBuiltAccessSet by youAgent and testsBuilding
ConnectionsBuiltAccessSet by youAgent and testsBuilding
Step 2

Build and test the agent

Senior U.S. engineers build the agent, its connections and its tests in your company’s own cloud account, such as AWS.

OwnerYouCode and docsYoursRuns itGnar or your team
OwnerYouCode and docsYoursRuns itGnar or your team
Step 3

Run it, or hand it over

You own the agent and its code. We can keep it running for you and rerun the tests each time it changes. Or we hand it to your team with the docs and walkthroughs they need.

Our record

Why Gnar?

Common questions

Frequently asked questions

Still have questions?

What does an AI agent development company do?

An AI agent development company builds software agents that do real work inside a company’s systems. An agent takes a request, works out the steps and does the work, sending anything unclear to a person. The Gnar Company is an AI agent development company. Our agentic AI development services cover every step, from mapping the job to building and testing the agent. Senior U.S. engineers build each agent in your company’s own cloud account. Then we run it or hand it to your team.

How is an AI agent different from a chatbot?

A chatbot answers questions. An AI agent does the work. A Gnar agent reads the request and makes the changes in your systems that you allow. Anything unclear goes to a person.

How is a custom AI agent different from AI automation?

AI automation reads orders and requests in any format and enters them the same way every time. An AI agent also decides what has to happen, then does it in your systems. It sends real judgment calls to a person. Take order processing. Automation reads each order and keys it in. A custom AI agent can also work out what an unusual order needs and act on it. The Gnar Company builds both.

What kind of companies need custom AI agents?

The Gnar Company builds custom AI agents for mid-sized companies. Their finance and operations teams do a lot of repetitive work by hand. Most have small tech teams, and many are manufacturers and distributors on NetSuite or a similar system. The work is usually a business workflow like the month-end close. Need an AI plan before any build? Start with Gnar’s AI Strategy & Fluency work: we help you write the plan and train your team.

Will an AI agent replace our staff?

Gnar builds agents to take the repetitive work, not the people. That means jobs like entering the same data twice. Your team keeps the judgment calls and approves the changes you flag. You decide where the freed-up time goes, such as serving customers or reviewing the agent’s work.

Can you build AI agents that work inside our existing systems?

Yes. The Gnar Company builds custom AI agents that work inside the systems you already use. That means NetSuite or your other ERP, your inbox and your shared files. We build the connections, often called integrations, that each agent needs. If the records it needs are messy, the discovery sprint finds that and says who fixes them.

What can an AI agent touch in our systems?

Only what you allow. You choose which records it can see and which changes need a person’s OK. Give it read-only access, and it can see records but never change them. Every action it takes in your systems is logged, so you can check what it did.

How do you make an AI agent production-ready, not just a demo?

Production-ready means it works every day on real work, not just once in a demo. The Gnar Company tests every agent on cases from your own past work, including the odd ones. Engineers call these tests evals. They run again each time we change the agent or its AI model. So if its scores drop, we see it before the change goes live.

What happens when an AI agent gets something wrong?

You can see what happened. Changes you marked for approval wait for a person. Every action the agent takes is logged, so any mistake can be traced. Requests the agent isn’t sure about go to your team. If the agent itself has a bug, we fix it free for the first 12 months. We add the case it got wrong to its tests, so they keep up with real work.

Who owns the AI agents you build?

You do. The Gnar Company builds each agent in your company’s own cloud account, such as AWS. You own its code too. We keep no ownership. After launch, we can keep it running for you. Or we hand it to your team with the docs and walkthroughs they need to run it.

Which AI models do your agents run on?

By default, Claude, made by Anthropic. The Gnar Company is a Claude Select Services Partner, which means Anthropic has vetted us to build with Claude. If your company already chose a different AI platform, we can build on that instead. When a model is retired or you switch models, the tests run again before the new one goes live.

Should we buy a pre-built AI agent instead of building one?

If a product fits your job, buy it, and we’ll tell you so. Gnar’s custom AI agents are for work that no product handles, or that a product handles only after heavy setup. The agent market is still young. So before you sign, test any product on your own past cases.

How does pricing work for an AI agent build?

The discovery sprint ends with a guaranteed price for each stage of the build. You know it before we start, and if it runs over, that’s on us. The sprint comes in three published sizes. Prices and lengths are on our Discovery page.

What does the guarantee cover?

Three commitments on every build engagement: a fixed milestone price with any overage on us, a guaranteed outcome meaning the software works as specified or we fix it, and a twelve-month bug-free warranty. It covers Discovery, Build, Forge and Maintain. It does not cover Embed. On Compass, Immerse and Integrate, ask us. In plain words: you know the price before we start, and we pay if it runs over. If it doesn’t do what we agreed, we fix it. Bugs found in the first 12 months get fixed free.

One jobShould an agent do it? We look first.RequestStepsSystemsPeople
One jobShould an agent do it?RequestStepsSystemsPeople

Start here

Bring us one job.

On the call, we’ll tell you straight whether an agent should do the job, and what the build involves. We’ll say an agent isn’t the fit if a product or your own team can do the job. Same if you only need a website chatbot. If it’s a fit, the next step is a discovery sprint that ends in a guaranteed price. Not sure which job, or need an AI plan first? We’ll help with that too.

Talk to us about AI agents

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