Box Mount Launches on Vercel Sandbox: A New Approach to AI Agent File Read/Write
Box Mount lets AI agents in Vercel Sandbox read and write Box files directly via the file system.
Box Mount is a new Box–Vercel Sandbox integration that mounts a Box folder into a sandbox directory, letting AI agents read and write cloud files with standard file operations instead of custom API code. Unmounting before the sandbox stops preserves all writes in Box, and separate user identities isolate Box credentials from the agent. The official contract review example shows AI Gateway reviewing a contract in the sandbox and saving results back to Box. The feature is in private preview via Box access request and targets enterprise document workflows.
Title
Box Mount Launches on Vercel Sandbox: A New Approach to AI Agent File Read/Write
Meta Description
Box Mount now supports running in Vercel Sandbox, allowing AI agents to read and write Box files through standard file operations, achieving automatic synchronization between sandboxes and cloud storage while keeping credentials isolated.
Article Content
AI agents in Vercel Sandbox can now directly read and write Box files through standard file system operations. The launch of Box Mount makes interactions between agents and cloud storage as natural as working with a local directory.
Core Mechanism: Mounting a Box Folder to a Sandbox Directory
Box Mount works in a straightforward way: it synchronizes a Box folder with a directory inside the sandbox. Any read or write an agent performs on files in the sandbox is reflected in Box in real time. The key step is "unmounting"—by performing an unmount operation before stopping the sandbox, everything the agent wrote is fully preserved in Box, even if the sandbox is subsequently deleted.
This design avoids the risk of the agent directly holding Box credentials. The sync process and the agent run as different sandbox users, keeping Box authentication information isolated from the agent's workspace. In other words, the agent can only see files under the mount point and cannot access the credentials themselves.
Vercel Sandbox is a cloud-based isolated compute environment launched by Vercel, designed specifically for running code generated or operated by AI agents. It provides ephemeral, fast-starting containerized sandboxes with support for file system persistence and network isolation. By default, an agent's file operations within the sandbox are confined to that runtime environment, and data is lost once the sandbox is destroyed. Box Mount exposes a bidirectionally synchronized mount point in the sandbox file system, enabling agents to read and write cloud files without directly calling the Box API, while leveraging the sandbox's user isolation mechanism to separate the sync daemon's runtime identity from the agent's.
Box is an enterprise-grade cloud content management platform that provides file storage, collaboration, and governance capabilities, and is widely used for centralized management of sensitive assets such as contracts and financial documents. Its API typically requires authentication via OAuth or JWT, and credential leakage poses a high risk. Box Mount encapsulates the sync logic as a separate process, so the agent can only access files under the mounted directory and cannot obtain Box access tokens.
Hands-On Example: Contract Review Workflow
The official contract review example demonstrates the complete chain: AI Gateway reviews a synthetic contract in Vercel Sandbox and then saves the review results back to Box. Throughout the process, the agent reads the contract text and writes review comments through the file system, while Box Mount handles the underlying synchronization.
For AI applications that need to process documents, this model eliminates the hassle of building a file transfer pipeline themselves. Agent developers do not need to write additional API call code to upload and download files; standard file operations are sufficient to complete the task.
AI Gateway is a unified model invocation gateway provided by Vercel that lets developers route requests across different large model providers and uniformly handle authentication, rate limiting, and observability. In the contract review example, AI Gateway sends the contract text to the model for review reasoning, Vercel Sandbox provides the execution environment, and Box Mount serves as the file read/write channel: the agent first reads the contract through the mounted directory, then writes the review results back to Box as files. This layered architecture decouples model invocation, code execution, and storage synchronization, making it easy to replace any component—for example, changing the model or storage backend without affecting the overall workflow.
Private Preview and Access
Box Mount is currently in private preview. Developers need to apply to Box for access, then configure it in Vercel Sandbox according to the Box Mount documentation. The documentation details the steps for mounting, synchronization, and unmounting.
From a product positioning perspective, Box Mount targets enterprise-grade AI workflow scenarios—contract review is just one example, and any task that requires an agent to read and write Box files can apply this model. The credential isolation design also meets enterprises' security requirements.
What It Means for Developers
Box Mount lowers the barrier for AI agents to integrate with Box storage. In the past, interactions between agents and cloud storage often required a custom middleware layer; now a single mount operation can bridge the gap. However, private preview means availability and stability remain to be seen, and interested teams can apply to try it early.
As AI agents take on more and more document processing tasks, infrastructure integrations like Box Mount will become increasingly important. The file system, as the interface most familiar to agents, is becoming a bridge connecting AI and cloud storage.
One-line Summary
Box Mount lets AI agents in Vercel Sandbox directly read and write Box files through the file system.
Paragraph Summary
Box Mount is a new integration between Box and Vercel Sandbox that mounts a Box folder to a sandbox directory, enabling AI agents to directly read and write cloud files through standard file system operations without writing additional API upload/download code. The key design is to perform an unmount operation before the sandbox stops, ensuring that written content is fully preserved in Box; meanwhile, the sync process and the agent run as different users, achieving Box credential isolation. The official contract review example demonstrates the complete chain in which AI Gateway reviews a contract inside the sandbox and saves the results back to Box. The feature is currently in private preview and requires applying to Box for access, mainly targeting enterprise-grade document processing workflows.
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