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Hermes Agent vs OpenClaw: Which Fits Your Work?

Short answer

Hermes Agent and OpenClaw are open-source agents under the MIT licence that run on your own infrastructure, and they suit different jobs. Hermes learns a process, remembers between sessions and works in the background on a schedule. OpenClaw is a personal assistant you reach from many messengers and devices. The licences cost €0, and a working agent with a server, a model and maintenance costs about €332 a month in our scenario.

How we workDetails ↓

  1. 01Call30 minutes with an engineer, free
  2. 02PrototypeA working system on your process and data, free
  3. 03ImplementationTarget and fixed price in the contract; 50% at signing
  4. 04Acceptance50% once the agreed target is met
net per agent for one process, build paid once
from €3,000
from signing the contract to acceptance
6–16 weeks
free prototype on your cases
€0
Book a free process review (30 min)

We belong to the OpenAI and Anthropic partner programmes and learn through their official courses. What this means ↓

Author: Syntalith · 3 min read

Example: the morning request inbox
Agent · ready

Statistics

Open-source AI agents: statistics 2026

392,716

GitHub stars for OpenClaw, against 256,096 for Hermes Agent. Both projects use the MIT licence. Popularity does not decide which one fits your process.

Figures checked: 22 October 2026

The decision in brief

DimensionHermes AgentOpenClaw
What it isAn agent that learns a process and works in the backgroundA personal assistant on your own devices
LicenceMITMIT
Main strengthSkills built from experience, memory between sessionsOne assistant across many messengers and devices
ChannelsTerminal, Telegram, Discord, Slack, WhatsApp, SignalMore than a dozen channels, apps, voice, Canvas
Long-running workScheduler, subagents, background workAn always-on assistant, sessions per channel
HostingA server from $5, GPU, serverlessYour own devices, a VPS, the cloud

Sources: Hermes documentation, Hermes repository, OpenClaw repository. At Syntalith we use both tools.

Where Hermes Agent is strong

Hermes has a closed learning loop. It creates skills after complex tasks, improves them as it works and builds memory between sessions. A built-in scheduler runs reports, backups and reviews without supervision, and subagents split work into parallel parts. It is a good choice when the agent is assigned to a process that should run better over time.

Where OpenClaw is strong

OpenClaw is a personal assistant for one person, running locally and always at hand. You talk to it in the messengers you already use. On macOS, iOS and Android it speaks, listens and shows a Canvas it controls. Its strength is reach across many channels, with sessions kept apart.

Hermes Agent vs OpenClaw: when to use which

  • The agent should learn a process and work in the background

    Hermes

    scheduler and memory

  • A personal assistant across many messengers

    OpenClaw

    reach and channels

  • A process with fixed steps

    an automation or an app with a model

    simpler maintenance

What they have in common

Both are open source, run on your own infrastructure and work with a model you connect yourself. Your data does not stay with you automatically, though. A cloud model, the tools and the channels are further paths for data. The same attack, for example prompt injection, affects both projects when permissions are too broad. That is why we assess them against the nine criteria of an agent.

What each of them costs

Scenario: your own agent on Hermes or OpenClaw
Licence
€0 (MIT)
Hetzner CX23 server
€5.49
Model, 300 tasks × 10 calls, Claude Sonnet 5.5
€24.10
Maintenance 2 h a week × 4.33
8.66 h = €302
Total
€332 a month
Time recovered, 300 tasks × 5 min
25 h = €873

€541 left a month

The number of tasks, the calls (2,000 input tokens and 500 output tokens each), the minutes saved per task and the maintenance time are the scenario's assumptions. €34.90 an hour is the EU average hourly labour cost for 2025 according to Eurostat. Server at Hetzner's price list from 15 June 2026. Model at Anthropic's rates, converted at the ECB rate of 1.1205 USD per euro on 22 October 2026.

Two routes to an agent

  • You set up the agent yourself

    €0 licence

    You configure it, update it and respond to failures. For a technical person with time.

  • An agent for the team

    from €3,000 net

    Agreed tools, permissions, a history of actions, acceptance and maintenance after the start.

If you run OpenClaw and want to try Hermes, the command hermes claw migrate makes the move easier. In a free 30-minute review we work out what you need and which option makes sense, or whether something simpler is enough. We build agents for teams as part of AI agents.

This is how we implement it in companies

All case studies →

Client results.

All projects →
foap.comcustomer service

foap.com customer service: 95% of replies are sent automatically.

Users from several countries write to foap.com, in several languages. The system reads the entire conversation and the terms of that person, and then sends a response in that person's language. Questions about money and exceptions go to the team with a ready draft, so they have to check and send them.

the system sends the answers itself, without human typing
95%
time from the arrival of the e-mail to the ready response (median)
30 s
e-mails that require a response receive a ready-made draft
100%
less work for every 1000 answers (estimate)
47 h

Data from foap.com production, October 20-21, 2026. Estimate: 3 minutes for handwritten response.

How foap.com customer service works →
Sample messages. Money matters always come to the person.

Other implementations

jaktako.design

studio projektowe

−87%

Time to look for new customers, every day

4 hours → 30 min

approx. 73 hours less per month (21 days of work)

according to the studio

How the agent loop works →
Signature Estates

real estate

approx. −90%

Operator time spent browsing portals, per day

2–3 hours → 20 min

approx. 45 hours less per month (21 days of work)

respect · contact the seller 5 minutes after the announcement

How the agent finds property listings →
Kuba Koziej, CEO and co-founder of MoreGrowth and board member at Natu.Care

Kuba Koziej

CEO and co-founder, MoreGrowth

„We started with my own AI agent. During the training that followed, I learned to build new applications myself. Today I am bringing this way of working with AI into my business. Working with Syntalith gave me exactly the skills and tools I needed.”

View the original training review on LinkedIn ↗

See the agent on your own cases before you commit.Book a free process review (30 min) →

How we build automation and agents

From a conversation to a working system in four steps.

  1. 01 · 30 min

    Free process review

    €0

    You're talking to an engineer. You receive the written plan within 2 business days.

  2. 02 · 5 days

    Free prototype

    €0

    The system works on 20-100 cases that your team has already handled. You see every result.

  3. 03 · 2–16 weeks

    Build

    50%

    Fixed price and goal written in the contract. First installment upon signing.

  4. 04 · after reaching the goal

    Reception

    50%

    You pay the second installment when the system reaches its target on your cases.

How a free prototype is created

Mon.

We set a goal

What result do you consider good?

Tue–Wed

The system is working

It goes through your affairs, one by one.

Thu

We compare

We check every difference with the team's work.

Fri

Result and price

List of errors and fixed implementation price.

You choose the matters. We anonymize them upon request, they stay in the EU and we delete them after the test.

On the market, such a test usually costs from PLN 3,000 to PLN 8,000.

Book a free process review (30 min)

We establish a prototype during a free analysis.

Data checked on October 25, 2026.

„Is my data safe?”

Yes. You choose where they go: from your company account to the model on your server.

  1. 00Employee's private account

    Customer and company data ends up in an account that the company cannot see or control. There is no data processing agreement, so it is a violation of the GDPR. When an employee leaves, the chat history goes with them.

  2. 01ChatGPT or Claude corporate account

    The provider does not use your data to train models. A copy of the queries remains in his logs for up to 30 days.

  3. 02API with zero retention (ZDR)

    The provider processes the request and does not save anything. It requires his consent, we prepare the application together.

  4. 03Processing in the EU

    Queries are counted and stored in Europe: OpenAI in the EU region, Claude via clouds with the EU region.

  5. 04Model at your place

    The open model runs on your server or in your cloud in the EU. The data does not go outside the company.

What we do with every implementation

  • Confidentiality agreement and data processing agreement before we receive any data.
  • You choose the cases for the prototype and we anonymize them upon request.
  • The data stays in the EU and we delete it after the test.
  • Corporate accounts with an administrator on your side.

When data cannot leave the company

The open model runs on your server or in your cloud in the EU. To choose from:

White-tailed eagle
Polish model, SpeakLeash and ACK Cyfronet AGH
PLLUM
Polish model, HIVE consortium commissioned by the Ministry of Digitization
Qwen
Alibaba
GLM
Zhipu AI
DeepSeek
DeepSeek

We select a model for the task and check it on your cases. We run it, tune it and maintain it.

Source: Bielik and PLLuM, ACK Cyfronet AGH ↗ · PLLuM, Ministry of Digitization ↗

Do you have a lot of your own data? We will fine-tune the small model.

  1. 1 Your examples
  2. 2 tuning
  3. 3 test on new cases
  4. 4 model at your place

When you have thousands of similar emails, documents or reports, we teach a small open model based on your examples. It works for you, responds quickly and costs less to maintain than a large model. We measure quality on issues that the model has not seen while learning.

Przemysław and Piotr did it in large programming and consulting companies. Artem did it before and does it today at Syntalith. It's about models on your own infrastructure, tuning and quality measurement.

Private AI models →

Source: OpenAI, training on data from private accounts ↗ · OpenAI, who sees conversations ↗ · Anthropic, changes for private accounts (August 2025) ↗ · OpenAI, data in API ↗ · AWS Bedrock, EU profile ↗

You choose the protection level during the interview. We sign the data processing agreement before we see any data.Schedule a free analysis →

AI agents

See the agent on your own cases before you commit.

The agent takes the case through the next steps in your systems, and the actions take effect until the consent of the indicated person is obtained. A prototype for 20-100 cases that your team has already handled costs €0. We write down the purpose and test set in the contract.

See AI agents →
net per agent for one process, build paid once
from €3,000
from signing the contract to acceptance
6–16 weeks
free prototype on your cases
€0
Book a free process review (30 min)

or call+48 888 78 48 78WhatsAppMon–Fri 9:00–17:00 CET

Questions

  • Hermes Agent or OpenClaw?

    Hermes, when the agent should learn a process, remember and do scheduled work in the background. OpenClaw, when you need a personal assistant always at hand, in many messengers and on your devices. When the process is simple, neither.

  • What licence do Hermes and OpenClaw use?

    Both projects use the MIT licence. According to GitHub (2026), OpenClaw has 392,716 stars and Hermes Agent has 256,096.

  • Can I move from OpenClaw to Hermes?

    Yes. Hermes has the command hermes claw migrate. After the move, check the tools, the permissions and the data.

  • How much does an agent on Hermes or OpenClaw cost?

    The licence costs €0. In our scenario a Hetzner CX23 server costs €5.49, the model for 300 tasks about €24 and maintenance €302, about €332 a month in total. At Syntalith we build an agent for a team from €3,000 net.

Let's talk

Just write, call or choose a date.

We work fast because we hate corporate cotton wool. We don't have salespeople or managers to keep an eye on managers. You talk immediately to engineers who then build your system. We respect each other's time and yours too.

We will accept 3 more companies by the end of the year.

Write
contact@syntalith.ai
Call
+48 888 78 48 78
WhatsApp
write on WhatsApp

Mon–Fri 9:00–17:00 CET

What our OpenAI and Anthropic partnerships mean for you.

OpenAI makes ChatGPT and Anthropic makes Claude. We belong to the partnership programs of both companies, so we work with their tools every day and learn from the creators themselves.

OpenAI Select PartnerClaude Partner Network
01We will select a tool for the task
We implement both ChatGPT and Claude. We check both on your documents, and you choose the one that makes fewer corrections and saves more time.
02Knowledge straight from the creators
We learn from official OpenAI and Anthropic courses and materials. Your team learns about the features and settings that work today.
03Licenses without our margin
When we roll out ChatGPT, Claude or Copilot, you buy the licences directly from OpenAI, Anthropic or Microsoft and they invoice you. We add nothing to the licence.
04Certified engineers
On the team, we have an AWS certification in machine learning and an Anthropic certification in systems architecture on Claude.

Participation in programs does not mean that OpenAI or Anthropic endorses our services.