Beeuni, E2B, and Daytona: choosing infrastructure for your agent product
Compare sandbox infrastructure with Beeuni’s computer for agents: ready-to-use tools, code execution, environment control, and multi-step agent work.
An agent researching suppliers may need to open websites, download price sheets, run Python calculations, and produce a report. An isolated environment gives the task somewhere to execute. Completing those steps also requires software, connected tools, and an agent runtime. Beeuni provides that computer, including code execution and environment customization, with the agent and its working tools already integrated.
What comes with the environment?
E2B provides sandbox infrastructure for running code and tools. Its code interpreter includes preinstalled libraries, and its coding-agent templates can start environments with an agent already installed. You can bring your model and orchestration framework, choose a template, and build your application around its execution APIs.
Daytona provides programmable sandboxes with files, processes, networking, snapshots, and environment configuration. It also offers Computer Use and agent integration guides. These services go beyond isolation: they give developers execution and desktop tools for building agent systems.
Beeuni supplies a computer prepared for an agent to work in. The standard environment brings together the agent runtime, a browser, a terminal, files, Python and JavaScript tools, and skills for common tasks. Project settings connect the agent to its model and authorized applications. A session then keeps the instructions, tool activity, and conversation together while the task runs.
The distinction is what your team has ready when it starts a task. With a sandbox service, you choose an execution environment or agent template and assemble the rest of the agent system around it. Beeuni integrates that running system, while still letting the agent execute your programs and use a customized environment.
| What you need | E2B | Daytona | Beeuni |
|---|---|---|---|
| Run code and manage files | Execution and filesystem APIs | Code, process, and filesystem APIs | Run scripts and commands, install task dependencies, and inspect files in the session |
| Prepare the environment | Code-interpreter environments, agent templates, and custom templates | Snapshots, custom images, and Computer Use environments | A standard agent environment, plus custom images and resource settings |
| Connect the agent to its tools | Use an agent template or integrate your chosen framework and tools | Use an integration guide or connect your chosen agent to sandbox tools | Configure agents, models, skills, and authorized tools within the project |
| Build around a running task | Combine sandbox operations with your agent and application state | Combine sandbox operations with your agent and application state | Send tasks and follow agent messages, tool events, and session state through the SDK or HTTP API |
Prepare the tools an agent actually needs
Being able to start a Python process does not mean a price-comparison task has everything it needs. The agent may also need a browser, spreadsheet libraries, document readers, and a way to produce a usable report. Beeuni’s standard environment includes browser automation, Python and JavaScript runtimes, and tools for common document, spreadsheet, PDF, and image work. It does not start each task from an empty operating-system image.
Skills give the agent instructions and helper scripts for particular jobs. For document work, a skill can explain how to use the installed libraries, run a conversion, and check the resulting file. You can add your own skills for your product’s formats and working rules.
A specialized dependency can still require installation, and a private application still needs authorization. The benefit is a prepared set of tools and an agent that can use them together. Your team adds what the task requires rather than assembling every basic runtime, file tool, and browser connection first.
Support the agent through a sequence of actions
An agent needs to see what happened after it acts. A command may fail, a page may load different content, or a generated file may need another check. Beeuni’s runtime carries the sequence of model requests, tool calls, and observations. The agent can read the error, change its approach, and continue within the same task. Your application can follow that activity through session events.
During screenshot-heavy browser tasks, Beeuni limits accumulated older images in model requests while retaining recent visual observations. For standard agent configurations, it reuses prepared dependencies or cached packages where possible instead of repeatedly downloading them at startup.
The session also gives the work a lifecycle your product can manage. You can read saved messages while the computer is stopped or reconnect to an ongoing session. If the computer is lost, you can continue the session on a new one using the saved conversation and pushed branch. Recovery does not restore lost, unsaved files or the old running processes. These distinctions are already represented in the session model instead of being left for each application to invent.
Follow a supplier comparison from website to report
Suppose your procurement product asks an agent to compare three suppliers. One publishes prices on a website, another offers a spreadsheet, and a third keeps the current quote in an email. The task needs browsing, file processing, calculations, and an authorized application connection. Returning three search snippets will not complete it.
In Beeuni, configure the agent’s model, skills, and application access, then start a session with the comparison criteria. The agent can inspect the website, read the spreadsheet and quote, write a script to normalize the prices, and run it. If the script encounters an unexpected column, it can inspect the file and revise the code. It can then produce a comparison with calculations and source references for review.
Your product submits the task, shows progress, and presents the result. Beeuni provides the running agent, its computer, and the tool execution needed along the way. You still decide which suppliers to include, what makes two offers comparable, and whether the report meets your requirements. With E2B or Daytona, you can build the same workflow; the difference is which agent configuration, tool connections, task state, and result handling your team assembles around the sandbox.
Keep control over code and the environment
Using Beeuni does not restrict you to predefined agent tasks. The computer can run your scripts, install task dependencies, work with repository files, and start applications you inspect through a preview. You can choose environment templates, custom images, and resource sizes for new computers. The agent-ready environment is a starting point you can extend.
Configure the model, instructions, skills, and tool permissions for the work you want to run. Connect the applications it needs, or add tools for your own service. Environment customization and agent configuration solve different problems, and Beeuni provides both. The Computer guide covers files, templates, resources, and previews; the agent guide covers behavior and access.
Summary
E2B and Daytona provide sandbox infrastructure and tools for running agent workloads. They suit developers who want to assemble their own agent runtime, tool connections, and task management around those environments.
Beeuni combines those execution capabilities with an agent runtime, prepared tools, model configuration, and application connections. Your product can submit a task and follow the agent as it works across websites, code, and files. You retain control over scripts, dependencies, and the environment.
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