Hermes Agent AI Development

Why AI Agents with Hermes

Hermes agent AI that runs in your own environment.

You have a Hermes model running in a test box, and it answers well when you poke it. Now you want it to handle a real job. The questions that decide it are not about the model. They are whether it can reach your records, whether you can tell why it did something last Tuesday, and whether the GPU bill makes sense at the volume you actually run. We build the part around the model that turns a self-hosted demo into a worker your staff rely on. That means retrieval over your own content, prompts and tools kept under version control, and an eval suite built from your real cases, so a Hermes agent stays dependable as you change it.

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Capabilities

What a production Hermes agent needs

Skills wired to your systems

Hermes agent skills are only useful when they call something real. We define each action the agent can take, bound it, and connect it to your APIs through the agent API so work happens inside the systems you already run, not in a sandbox.

Grounded retrieval over your content

We connect the agent to your documents, records and knowledge bases on infrastructure you control, so its answers come from your business and neither the question nor the data leaves your environment.

Versioned prompts and decisions

The prompts, the tools the agent can reach, and the choices behind it sit under version control. When behaviour drifts you can see what changed and roll it back, the same way you manage code.

Evals built from your real cases

We turn your historical examples into a test suite that scores the agent before launch and after every change, so reliability and cost are measured against your work rather than assumed from a benchmark.

Where this leaves you stuck

You got a Hermes model running, maybe in Docker, maybe on a spare GPU box, and it gave good answers in a quick test. That is the easy part, and it is also where most teams stall. The model on its own knows the public internet, not your pricing, your contracts or your case history. It cannot reach the system that holds the answer, and when it gets something wrong you have no record of why. So the prototype that impressed everyone in the meeting never makes it in front of staff, because nobody can vouch for it on the day it slips up.

The pull towards self-hosting Hermes is usually one of three things. Your data cannot go to a hosted API. You want control over the model rather than a vendor’s release schedule. Or your volume is high enough that per-call pricing on a hosted model has started to hurt. Those are good reasons. They are also the moment the work shifts from the model to everything around it.

Why the model alone under-delivers

Running open weights gets you a capable engine and nothing that makes it a worker. The reasoning is fine. What is missing is the part that connects it to your business and keeps it honest over time.

An agent that cannot read your real records is just a confident guess. So the first piece of real engineering is retrieval over your own content, kept inside your environment so neither the question nor the data leaves it. This is principle #5, AI-accessible internal data, applied here in a specific way. Because you self-host, the retrieval layer runs next to the model on hardware you control, which is the whole point of choosing Hermes over a hosted option.

The second gap is traceability. When a self-hosted agent gives a wrong answer, you own the fix, and you cannot fix what you cannot see. So we keep the prompts, the tools the agent can call, and the design choices behind it under version control, the way we manage code. That is principle #6, version-controlled prompts and decisions. Every change is recorded and reversible, which matters more when there is no vendor support desk to fall back on.

A self-hosted Hermes agent retrieving from internal records on GPU hardware inside a private network, with a person reviewing its output

The third gap is platform discipline. A notebook that answers once is not a service that answers ten thousand times. That is principle #9, quality internal platforms, and self-hosting makes it non-negotiable, because the scaling, the health checks and the cost monitoring are now yours rather than a managed API’s. You can read more about these foundations in our approach.

How we deliver it for Hermes specifically

We start with one workflow and agree what good looks like on your own work before we build anything. Then we size the model variant and the GPU footprint to that task, rather than reaching for the largest Hermes model and the biggest box. Right-sizing is where most of the self-hosting cost is won or lost, so we do it first and in writing.

From there we wire the agent’s skills to your systems through its agent API, bound each action it can take, and ground it in your content with retrieval. We test it on your real historical cases, release it to a small group, and expand once the numbers hold. The monitoring, logging and alerting we stand up are yours to keep, because you own the running of it once we hand over.

When Hermes is the right call, and when it is not

A Hermes agent is the right choice when data has to stay inside your environment, when you want control over the model itself, or when your volume makes per-call pricing painful, and you can run the infrastructure. It is the wrong call when you would rather a managed service handled hosting and scaling, when your volume is too low to justify owning GPU hardware, or when a task genuinely needs a hosted frontier model’s hardest reasoning. We treat the model as a means to your outcome, not a default, and we will recommend a managed option when it serves you better.

See the broader service in AI Agents, and compare framework options across our technologies. Where data residency and control drive the decision, it often applies in FinTech & Banking, Healthcare and Government.

Explore further

Read more about our AI Agents service and the Hermes technology.

How this looks in practice

Representative solutions.

All solutions

Approvals cleared

AI agents for construction companies, working the approvals backlog

Faster review

How a mid-size law firm reads every contract with a Claude legal assistant

Faster replanning

An agentic dispatch assistant that never sleeps for a logistics operator

No stupid questions

Frequently asked.

Can a Hermes agent use GitHub Copilot?

They solve different jobs, so they sit side by side rather than inside each other. GitHub Copilot helps your developers write code in the editor. A Hermes agent is the worker you self-host to run a business task in production. We often build the agent while your team keeps using Copilot to ship the supporting code, and we keep the agent's prompts and tools version-controlled regardless.

Why is Hermes so expensive?

With a Hermes agent the model weights are open, so the cost is not a per-call licence. It is the infrastructure you run it on. Capable GPU hardware, on-premises or in your own cloud account, adds up at volume. We size that to your task before you commit and tell you plainly if a hosted model would be cheaper for your case. That honesty is part of our approach.

Does a Hermes agent have a web UI?

Out of the box you interact with it through its agent API rather than a polished web interface, and any chat front end you have seen is something built on top. For most clients we put the agent behind an interface your staff already use, such as an internal tool or a help desk, so people do not learn a new screen to get value from it.

Does a Hermes agent have a heartbeat or health check?

It depends on how you deploy it, because self-hosting means you own the monitoring. We set up health checks, logging and alerting you control when we build, so you can see whether the agent is up, how it is behaving and what it is costing once it is live. That visibility is the trade you accept for keeping everything in your environment.

What is a Hermes agent and when is it the right choice?

It is an AI agent built on the open Hermes models, run on infrastructure you control rather than a third-party host. We reach for it when you need data to stay inside your environment for residency, control or cost-at-volume reasons and you can run the hardware. When a managed service would serve you better, we say so.

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Scope a self-hosted Hermes agent

Tell us the workflow you want a Hermes agent to handle and where your data has to stay. We will assess whether self-hosting fits, what it takes to run, and whether a managed option would serve you better.