# Agent37: Managed AI Hosting and Isolated Sandbox Environments A platform enabling scalable, white-label AI agent deployment with granular compute-based billing. - **Source:** [Dynamic Business](https://dynamicbusiness.com) - **Published:** 2026-10-20 - **Topic:** [Software & Engineering](https://brifing.si/c/engineering) - **Original article:** - **On Brifing:** https://brifing.si/s/13dced89-95ae-4c29-ac18-afd5e24fe7d8 ## Isolated Sandbox Architecture Agent37 provides managed hosting where each AI agent operates within a dedicated, isolated sandbox environment. This architecture ensures persistent files, memory, and runtime stability for automated workflows. By handling kernel-level isolation behind the scenes, the platform removes the infrastructure overhead typically associated with deploying and managing complex, multi-modal AI agent systems. ## Multi-Modal Operational Capabilities Agents on the platform possess extensive capabilities, including internet access, shell command execution, and Python script processing. The environment supports file manipulation for formats like CSV and PDF, alongside a visual file browser and live Linux desktop. These features allow developers to build sophisticated agents that perform complex tasks beyond simple text generation. ## Integration and Automation Ecosystem The platform facilitates over 1,000 application integrations through Composio, connecting agents to tools like Gmail, Slack, and GitHub. Users can configure scheduled cron-like tasks, webhooks, and metrics tracking. Additionally, public ports enable the embedding of custom user interfaces or front-end applications directly into the agent’s operational workflow for seamless business deployment. ## White-Label API-First Strategy Businesses can leverage the Cloud API to provision always-on agents for individual customers under their own brand. The white-label Starter Kit allows companies to maintain the billing relationship while scaling agent-powered products. This approach is specifically designed for SaaS startups that need to deploy per-customer assistants without managing underlying server infrastructure. ## Security and Privacy Standards Data privacy is maintained by ensuring user prompts, terminal sessions, and files are never used for model training. All data remains encrypted both in transit and at rest. The platform currently holds SOC 2 Type I certification, with Type II certification currently underway to further validate their commitment to enterprise-grade security standards. ## Usage-Based Financial Model Agent37 eliminates fixed per-seat fees in favor of a prepaid balance system consumed by compute and storage usage. Rates are calculated per minute, with examples including $0.0011 per vCPU-hour and $0.00096 per GB RAM-hour. This transparent pricing structure allows users to avoid lock-in and manage costs by deleting sandboxes when they are inactive. ## Tiered Resource Configurations Plans range from the Basic tier at $3.99 per month to the Max tier at $99.99 per month. Resource allocations scale from 1 vCPU and 4 GB RAM up to 4 vCPU and 16 GB RAM. Higher tiers include built-in Chromium browsers, dedicated onboarding, team roles, and additional AI credits for bundled models. ## Strategic Value for Builders Agent37 serves as a practical middle ground between basic chatbot platforms and full-scale infrastructure builds. By combining persistent sandboxes with flexible, metered pricing, it lowers the barrier for deploying agent-based products. Decision-makers should evaluate this platform when control, data privacy, and white-label branding are critical requirements for their automation and AI initiatives. ## Sources covering this story - https://dynamicbusiness.com/ai-tools/agent37-managed-ai-hosting-isolation.html — --- _Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._