Agent 37

As a freelancer constantly exploring the latest AI tools to boost my productivity and offer cutting-edge services to clients, I'm always on the lookout for platforms that simplify complex tech. Recently, I stumbled upon a new launch that caught my eye: Agent 37. It promises to "give every customer their own Hermes or OpenClaw agent," and let me tell you, after diving deep, this isn't just another flashy AI tool. It’s a game-changer for anyone wanting to deploy persistent, intelligent AI agents without getting bogged down in server management.

What is Agent 37 and What Core Problem Does It Solve?

Imagine you have a brilliant idea for an AI agent – maybe it's a super-smart customer support bot, a personalized market scanner, or an automated lead generation assistant. You've heard about powerful open-source agents like OpenClaw and Hermes Agent, which can truly "get things done" by interacting with the real world, running commands, and learning over time. But then reality hits: setting up and maintaining these agents often means wrestling with Virtual Private Servers (VPS), Docker containers, complex configurations, and constant "babysitting" of the infrastructure.

This is exactly where Agent 37 steps in. Launched on Product Hunt on June 21, 2026, Agent 37 is a managed hosting platform designed to take all that infrastructure headache away. It provides fully managed, isolated containers for your Hermes, OpenClaw, or even ClaudeCode agents. Instead of you building and maintaining the backend, Agent 37 handles it all. Their goal is to let you deploy a dedicated, always-on AI agent for each of your customers with just a couple of API calls, all under your own brand.

For freelancers and small agencies, this solves a massive problem: how to offer sophisticated, personalized AI agent services to clients without needing a dedicated DevOps team or spending countless hours on server upkeep. It abstracts away the complexity of infrastructure, letting you focus on what you do best: building and delivering value with AI.

How Does It Work – The Main Workflow Explained

The core idea behind Agent 37 is simplicity and isolation. Here’s a breakdown of its main workflow:

1. Provision an Instance: You start by making a single API call to Agent 37. This call provisions a dedicated, isolated container for your customer's AI agent. Think of it as spinning up a mini-computer just for that agent. Agent 37 supports templates for popular agents like Hermes and OpenClaw, so you don't start from scratch.
2. Agent Comes Alive: Once provisioned, your chosen agent (e.g., Hermes or OpenClaw) comes online with its own unique URL. This agent is "always on" and maintains its state – files, memory, and connected accounts – persistently between conversations until you decide to delete it.
3. Interact via API: You then interact with this agent using another simple API call. This allows your application or client-facing interface to send messages to the agent and receive its responses. Agent 37 handles all the routing and streaming of data, so you don't have to worry about network configurations or proxies.
4. Browser-Based Management: For more hands-on control, Agent 37 offers a web-based dashboard with a full TTY terminal, a visual file browser, and even a live desktop. This means you can install packages, edit configs, tail logs, upload files, and even watch your agent browse the web in real-time, all from your browser.
5. Bring Your Own Keys: For the underlying Large Language Models (LLMs) that power these agents (like GPT, Claude, or Gemini), you bring your own API keys. This ensures your data and costs are directly managed with the LLM providers, and Agent 37 never touches your sensitive keys.

Essentially, Agent 37 provides the robust, "always-on" environment that these autonomous agents need to thrive, without you having to be a server administrator. It's a powerful abstraction layer that makes advanced AI agent deployment accessible.

Key Features – Real Freelancer Use Cases

Let's talk about the features that make Agent 37 truly shine, especially from a freelancer's perspective:

• Managed OpenClaw and Hermes Hosting: This is the bread and butter. As a freelancer, running OpenClaw or Hermes locally or on a basic VPS means constant monitoring, updates, and troubleshooting. Agent 37 manages all of this, providing isolated, dedicated containers. This means less time on infrastructure and more time building custom solutions for clients.
  • Freelancer Use Case: I can offer a client a dedicated AI agent that manages their social media interactions, responds to customer queries, or even performs market research, all without them needing to know anything about servers. I just provision an instance, configure the agent, and integrate it into their workflow.
• Browser-Based Terminal, File Browser, and Live Desktop: This is a godsend. Full terminal access in your browser means you can fine-tune agent configurations, install specific libraries, and debug issues without SSHing into a server. The live desktop feature is particularly impressive, allowing you to watch the agent interact with web applications in real-time, which is crucial for complex automation tasks.
  • Freelancer Use Case: Setting up a new skill for an OpenClaw agent that requires installing a Python package? I can do it directly from the browser. If a client's agent is supposed to scrape data from a website, I can visually confirm it's working correctly via the live desktop.
• Extensive Integrations (1000+ via Composio): Agent 37 boasts integration with a massive ecosystem of apps including Gmail, WhatsApp, Slack, GitHub, Notion, and Trello. This is vital for AI agents that need to interact with various services to be truly effective.
  • Freelancer Use Case: I can build an agent for a marketing client that monitors their Slack channels for specific keywords, drafts email responses in Gmail, and updates tasks in Trello, all seamlessly connected through Agent 37.
• API-Driven Deployment and Messaging: The ability to provision and interact with agents via a simple REST API is powerful for building scalable solutions. You can integrate Agent 37 directly into your client's existing applications or build custom dashboards.
  • Freelancer Use Case: For an enterprise client, I can build a custom internal tool that allows their team to dynamically spin up specialized agents for various projects, each with their own isolated environment and specific capabilities, all managed through a central interface I developed.
• Persistent Agent Memory and State: The agents hosted on Agent 37 aren't stateless chatbots. They remember past conversations, maintain files, and keep connected accounts active. This is crucial for agents that learn and adapt over time.
  • Freelancer Use Case: An AI research assistant I build for a client can maintain a knowledge base of previous findings, learn their preferences, and continuously refine its research strategy across multiple sessions, acting like a true digital colleague.
• White-Labeling Capabilities: Agent 37 is built with agencies and resellers in mind, offering white-label features. This means you can offer these powerful AI agent services under your own brand, giving your clients a consistent experience.
  • Freelancer Use Case: I can brand the entire AI agent solution as my own, providing a professional, integrated service to my clients without them ever seeing "Agent 37." This enhances my agency's credibility and perceived value.
• Minions Task Board: This built-in task board allows you to assign work, review agent outputs, and schedule recurring jobs. It’s a workflow management system specifically for your AI agents.
  • Freelancer Use Case: If I have an agent generating reports or drafting content, I can use the Minions task board to review its outputs before they go live, ensuring quality control and making necessary edits.

Pricing – Simple and Transparent

One of the most attractive aspects of Agent 37 is its pricing model, which aims to be both accessible and transparent. They emphasize "pay for compute, not seats," which is great for scaling.

For individuals and direct users, the pricing is incredibly competitive:

• Basic Instance: Starts at just $3.44/month. This includes 1 vCPU, 3GB RAM, and 6GB Disk, which is more than enough for many personal or small-scale agent deployments. Other sources mention $3.99/month for 1 vCPU + 4GB RAM.
• First Instance Free: You can try out Agent 37 without needing a credit card for your first instance. This is a fantastic way to experiment and see if it fits your needs.

For agencies and those looking to white-label, there are slightly different tiers, often referred to as "Agent 37 Cloud" pricing, which also reflect the underlying compute resources:

Tier (for Resellers/White-label)	vCPU	RAM	Monthly Cost
Standard	2	4 GB	$4.99/month per instance
Advanced	4	8 GB	$9.99/month per instance
Pro	8	16 GB	$14.99/month per instance

You bring your own API keys for the underlying AI models (like OpenAI, Anthropic, or Google Gemini), so those costs are separate and directly managed by you. Agent 37 allows you to meter models from the same prepaid balance with per-instance spend caps, giving you excellent cost control.

What Makes It Unique Compared to Similar Tools?

In a rapidly evolving AI landscape, uniqueness is key. Agent 37 stands out in several ways:

• Focus on Open-Source Agents: While there are many AI agent platforms, Agent 37 specifically targets managed hosting for powerful open-source agents like OpenClaw and Hermes. This is a crucial distinction. Many platforms offer proprietary agents or frameworks, but Agent 37 leverages the flexibility and community support of established open-source projects, which are known for their ability to perform complex, real-world actions.
• Infrastructure Abstraction at a Low Cost: The primary differentiator is removing the "babysitting servers" aspect of running persistent AI agents. Compared to self-hosting OpenClaw on a typical VPS (which can cost $20/month or more for basic hosting), Agent 37 offers a fully managed, isolated container for as little as $3.44-$3.99/month. This makes advanced agent deployment incredibly accessible.
• White-Labeling by Default: For agencies and founders building vertical AI products, the white-label capability is a huge advantage. You can present the entire solution under your brand, making it seamless for your clients. This is often an expensive add-on or not available in many competitor offerings.
• Comprehensive Browser-Based Environment: The combination of a web terminal, file browser, and live desktop within the browser is quite robust. It provides a level of control and visibility that's often missing in simpler managed AI services, bridging the gap between a fully managed black box and raw VPS access.
• API-First Approach for Multi-Customer Deployment: Agent 37 is designed from the ground up for developers and founders who want to deploy multiple, customer-specific agents programmatically. The "one API call to provision, another to message" workflow simplifies scaling agent-based services.

Who Should Try This?

• Freelancers and Consultants: If you're building custom AI solutions for clients and want to integrate autonomous agents without managing infrastructure, Agent 37 is perfect. It lets you focus on solution design and client delivery.
• Founders of AI Startups/Vertical SaaS: For those creating niche AI products (e.g., a "CEO agent," a "clinic agent," or a "legal agent" for specific industries), Agent 37 provides the backend to deploy and manage these agents for your customers efficiently.
• Agencies Offering AI Services: With its white-label capabilities and multi-instance management, agencies can easily offer branded AI agent solutions to their clients, scaling up as needed.
• Developers Experimenting with Autonomous Agents: If you've been keen to try OpenClaw or Hermes but found the setup daunting, Agent 37 offers an incredibly low-friction way to get started and experiment. The first instance is free!
• Anyone Seeking Cost-Effective Persistent AI: If you need an AI agent that runs 24/7, remembers context, and performs actions, but don't want the high cost of a dedicated server or complex cloud setup, Agent 37's pricing is very appealing.

Who Should Skip This?

• Organizations with Extreme Security Compliance Needs (Without Further Verification): While Agent 37 states data stays in your container and API keys go direct to providers, one review noted a lack of detailed security documentation, third-party audits, or specific data retention policies. If your organization requires stringent, documented compliance (e.g., HIPAA, GDPR with specific audit trails) and cannot verify these details, you might need to investigate further or consider alternatives with more extensive security certifications. However, Agent 37 does mention kernel-level isolation with gVisor and uses Google Gemini with built-in safety filters.
• Users Needing Deep Infrastructure Customization: If you require full root access to the underlying server operating system, or need to run highly specialized, non-containerized software that isn't compatible with a managed container environment, Agent 37 might be too abstracted for your needs.
• Those Unwilling to Bring Their Own LLM Keys: Agent 37 requires you to bring your own API keys for the large language models. If you prefer an all-inclusive solution where LLM costs are bundled, this might be a minor inconvenience.

Final Verdict

Agent 37 is a breath of fresh air for anyone looking to harness the power of autonomous AI agents without the traditional DevOps overhead. It democratizes access to sophisticated agent technologies like OpenClaw and Hermes, making them accessible to a much broader audience of freelancers, founders, and agencies. The low cost, comprehensive browser-based management, and white-labeling capabilities are significant advantages.

While some users might desire more extensive security documentation or deeper infrastructure control, for the vast majority of use cases involving deploying customer-specific AI agents, Agent 37 hits the sweet spot between power, ease of use, and affordability. It's a tool that genuinely empowers you to build and scale intelligent AI services with minimal friction.

Rating: 9/10 – A truly impressive launch that solves a real pain point in the AI agent ecosystem.

Frequently Asked Questions

What types of AI agents can I host on Agent 37?

Agent 37 is designed to host persistent AI agents like OpenClaw, Hermes, and ClaudeCode. These are powerful, often open-source agents capable of performing real-world actions, not just generating text.

Do I need to have my own AI model API keys to use Agent 37?

Yes, Agent 37 operates on a "bring your own API keys" model for the underlying Large Language Models (LLMs) such as OpenAI's GPT, Anthropic's Claude, or Google's Gemini. This allows you to manage your LLM costs and data directly with the providers.

Can I white-label the AI agents I deploy through Agent 37 for my clients?

Absolutely. Agent 37 offers white-labeling capabilities, allowing you to deploy and manage AI agent instances for your clients under your own brand. This is a significant advantage for agencies and vertical SaaS businesses.

What kind of resources does a basic Agent 37 instance include?

A basic Agent 37 instance typically includes 1 vCPU, 3-4GB of RAM, and 6GB of disk space, starting from $3.44-$3.99 per month. This provides an isolated, fully managed environment for your AI agent.