Automation & AI · Open-source autonomous agent framework
Hermes Agent
integration & API.
MIT-licensed agent framework by Nous Research — we build the custom skills and supervision layers around it.
HA What is Hermes Agent?
Hermes Agent in plain English.
Hermes Agent is an open-source AI agent framework released by Nous Research under the MIT licence. Per the project documentation, it supports models via Nous Portal, OpenRouter (200+ models), custom OpenAI-compatible endpoints, and local vLLM inference. The framework provides persistent memory, parallel sub-agents, scheduled automations and a skill system via SKILL.md files. The hermes-agent.org site is the authoritative source for current capabilities and documentation.
What businesses use it for
Common Hermes Agent
use cases.
- 01 Workflow automation against business APIs with persistent agent memory
- 02 Local-inference agent deployment for confidentiality-sensitive workloads
- 03 Scheduled automations (cron-style) for repeating workflows
- 04 Multi-agent coordination on long-running tasks
- 05 Custom skill development for specific business processes
- 06 Integration layer between business systems and AI agent logic
Why custom?
Beyond the default Hermes Agent integrations.
Hermes Agent is an open-source autonomous agent framework released by Nous Research in February 2026. Documentation describes provider-agnostic model support, persistent agent memory, a SKILL.md extension format, and design choices including local data storage and container hardening. In our experience, those architectural defaults make Hermes Agent a sensible starting point for organisations whose workflows involve sensitive data and where the local-inference / local-data posture is load-bearing. We build the custom skills and supervision layers around Hermes Agent that any production deployment needs — integration with your business systems, structured handoff points where a human reviews before action is committed, and audit logging shaped to the workflow.
What we build with Hermes Agent
Common Hermes Agent integrations.
Custom SKILL.md development tying Hermes Agent into your business APIs
Workflow design that defines where the agent acts autonomously and where a human must approve before action
Integration with practice management, CRM, or accounting platforms via their APIs
Architectural advice on model selection (Hermes-family models, Claude, OpenAI, local vLLM) given the workflow's data-handling needs
Operational guardrails — supervision gates, audit logs, error handling — designed for the workflow
Migration planning for moving manual or rule-based workflows onto an agent framework
Commonly paired with
Hermes Agent works with the rest of your stack.
How we build
Production-grade.
Not Zapier in a trench coat.
Every Hermes Agent integration we ship handles failure properly: idempotent jobs, retry logic, dead-letter queues for unrecoverable cases, and observability so you can see exactly where data is at any moment.
Tested
Real test suite, real edge cases. Not just "it worked once."
Observable
You see what is happening — events logged, errors surfaced.
Maintainable
Documented, version-controlled, handed over properly.
More Automation & AI
Other automation & ai platforms we connect.
Z Zapier
Zapier integrations and the moments when custom code is the cheaper answer.
M Make
Make (Integromat) integrations and migrations to more reliable architectures.
N n8n
n8n integrations and self-hosted automation for businesses that want control over their data.
OpenAI
OpenAI integrations engineered for production — not demo-ware that breaks at the second edge case.
FAQ
Common questions about Hermes Agent integration.
Is Hermes Agent suitable for regulated industries?
In our experience, Hermes Agent's architectural posture — local data storage, container hardening, model-agnostic inference including local vLLM — is a more defensible starting point for regulated industry workflows than frameworks built primarily around remote-API consumer assistant patterns. That said, suitability for a specific regulated workflow depends on the industry framework (for example, ASCR confidentiality obligations for Australian legal practitioners, Privacy Act for personal information generally) and how the deployment is configured. We design custom builds with supervision points and audit logging where the workflow requires it; the final assessment of regulatory fit is for the organisation and their professional advisers.
What's the difference between Hermes Agent and the Hermes model family?
Hermes Agent is the framework (released February 2026, MIT-licensed) — the runtime that defines and executes agents. The Hermes model family (Hermes 3, Hermes 4, also from Nous Research) is a set of open-source language models fine-tuned for function calling and agentic workflows. They are designed to work together but are distinct products: Hermes Agent can run on Hermes models, Claude, OpenAI, or local-vLLM models per the project documentation.
How does Hermes Agent compare with OpenClaw?
Both are open-source agent frameworks released in 2026. Per their respective documentation, Hermes Agent is positioned as a developer-facing autonomous agent runtime with emphasis on local data storage, container hardening, and provider-agnostic model support, and OpenClaw is positioned as a personal AI assistant product with a consumer-style integration set. We work with both. The choice between them depends on the specifics of the workflow, and each project's documentation at hermes-agent.org and openclaw.ai is the authoritative source on current capabilities.
Can Hermes Agent integrate with a legal practice management platform like LEAP?
Yes, in principle — Hermes Agent's skill system can be extended with a SKILL.md that calls a platform's public API. We build these integrations as bespoke custom skills, with supervision gates appropriate to the workflow being automated. Any deployment involving privileged or confidential matter content should be assessed against the firm's professional obligations (for Australian solicitors, the Australian Solicitors' Conduct Rules apply) and is a decision for the firm and its advisers.
Related reading
Thinking we’ve published on this kind of work.
Agentive AI in Australian legal practice: what's possible, what's gated, and what isn't yet
A working overview of where autonomous AI agents fit in Australian law-firm operations today — the frameworks (OpenClaw, Hermes Agent), the model question, the LEAP API surface, and the licensing and regulatory constraints that shape what can actually be built.
AI digital marketing agencies in Adelaide: where AI actually helps (and where it doesn't, yet)
An honest look at what an AI-led digital agency in Adelaide can and can't do for Australian businesses right now — and the questions to ask before you sign anything.
What AI actually costs to run in production
AI demos are cheap. Production is not. Where the money actually goes when you ship an AI feature, and how to size the engineering investment around the model.
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