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AI Agents for Business: Build and Integrate Virtual Assistants with Hostman

AI Agents for Business: Build and Integrate Virtual Assistants with Hostman
Hostman Team
Technical writer
News

Hostman now offers a fully managed AI Agents service that allows to create and deploy virtual assistants powered by generative AI models. Whether you need a support chatbot, an internal assistant, or a data-driven reporting tool, AI Agents can be configured, tested, and integrated from the Hostman platform.

The service is designed to give teams flexibility: from quick API integration to embedding a ready-to-use chat widget into a website or product. Everything is managed directly from the Hostman Control Panel.

AI Agents

What You Can Build with AI Agents

AI agents are flexible by design. They can function as public-facing chatbots embedded in a website or as internal assistants integrated into business tools.

We’ve prepared some common scenarios:

  • Customer-facing assistants that provide consultations in chat format;

  • Internal bots that analyze uploaded data and generate summaries;

  • Onboarding assistants that guide new employees through training materials;

  • AI-powered endpoints inside SaaS products.

You are not limited to generic responses. Agents can use your own knowledge base, ensuring answers are aligned with your documentation, product logic, and company policies.

Knowledge Bases and External Tools

An AI agent becomes much more useful when it understands your context. With Hostman, you can create and connect knowledge bases so the model generates responses grounded in your own data.

Beyond that, the platform supports MCP (Model Context Protocol). MCP allows agents to work with external tools rather than relying only on stored knowledge. Through an MCP server, an agent can perform web searches, connect to services like Notion, interact with documentation systems, or manage a browser session.

The agent itself does not need to understand how those services are structured. It simply uses the tools made available by the MCP server and incorporates the results into its response. This approach makes it possible to build advanced workflows without turning your AI integration into a complex engineering project.

Integration Options: API and Chat Widget

Once your agent is configured, you can use it in different ways.

Each agent receives its own API endpoint. Hostman supports two API formats:

  • OpenAI-compatible API for integration with existing libraries and interfaces;

  • Native API for simpler, faster integration without additional dependencies.

This means your AI agent can connect to tools that already support the OpenAI API, including developer environments like VS Code extensions.

If you do not need a backend integration, you can embed the agent directly into a website or application using a chat widget. This allows you to launch an AI-powered assistant without writing complex server-side logic.

Full Control from the Playground to Production

Before deploying an agent, you can test and fine-tune it in the built-in Playground. This sandbox environment allows you to experiment with system prompts, validate how the knowledge base influences responses, and check how the model behaves under different inputs.

You can also attach text files and images, review chat history, manage access keys, and configure endpoints. Agents can be suspended temporarily or deleted at any time. If your usage grows, you can upgrade the plan or purchase additional token packages for the current month without changing your existing configuration.

All of this is handled inside the Control Panel, giving you full visibility and control over how your AI assistant operates.

Pricing, Tokens, and Scaling

AI agents rely on large language models, and usage is measured in tokens. The documentation clearly explains how tokens are counted, which models are available, and how pricing works.

When your workload increases, you can scale in a predictable way. Upgrade the agent’s plan or add more tokens without disrupting production. This makes it easier to experiment, launch, and then grow usage gradually as your product evolves.

How to Get Started

To create your AI agent on Hostman: 

  1. Log in to the Control Panel
  2. Go to the AI Agents section and click Create Agent or Add.
  3. Select the AI model for the agent. After the agent is created, the model cannot be changed.
  4. Choose a pricing plan based on the required number of tokens. You will be able to upgrade the plan later, but downgrading will not be possible.
  5. Provide a prompt for the agent. The prompt explains what the agent should do.

The control panel includes several example prompts. You can review them to understand the recommended format or use them as a starting point and adjust them to your needs.

  1. Connect an existing knowledge base or create a new one. You can also add it later in the agent settings.

Knowledge bases allow agents to generate more complete and accurate responses based on the data you provide. Examples of knowledge bases include product documentation, pricing information, or product catalogs.

  1. Fill in the agent information: a convenient name and a comment.
  2. Review all selected parameters, check the service cost, and click Order.

Deployment will take a few minutes. After that, you can start working with the agent.

If you need guidance at any step, the documentation provides detailed instructions on configuration, models, pricing, and API usage.

Feel free to check our detailed instructions in the Documentation; and if your scenario requires a faster answer, our 24/7 live support team is ready to assist you directly in the online chat.

Bringing AI Into Your Workflow

Hostman AI Agents are designed for teams that want practical results. Whether you are building a customer support assistant, enhancing your SaaS product with AI endpoints, or creating internal automation tools, the platform gives you the structure to move from idea to production smoothly.

You control the prompts, the data, the integrations, and the scaling. Hostman provides the infrastructure and the tools to make it work reliably. Deploy your first AI assistant in a couple of clicks.

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