Per-user isolated environments for AI agents
The enterprise agent platform. Build, test, evaluate, run, and improve AI agents on one runtime, with cost per customer and a complete audit trail.
Per-user isolated environments for AI agents launched on April 7, 2026 with 13 votes, #1,135 of 21,248 launches that month and more than 90% of that year's launches.
In plain words
Oncell provides per-user isolated environments designed for AI agents. The platform enables developers and organizations to deploy AI agents with separate, secure environments for each user, preventing data cross-contamination and ensuring privacy. This approach stands out by offering isolation as a core infrastructure feature rather than an add-on, making it suitable for teams building multi-user AI agent applications that require strong data separation and security boundaries.
written from the facts on this page · September 2026
From the sources
One platform to build, test, evaluate, and run your agents. Every run is a trace, every trace is a test, every test is a reward. Post-train models you own on the work your agents already do. Built by a team that ran infrastructure for sandboxes, training, and inference at AWS, Google, Rubrik, and NVIDIA. One agent built, run, scored, and compared across models, in the console. Every agent action crosses one boundary. That boundary is the trace, the test, the reward, and the audit trail at once. import { Agent , tools } from "oncell" ; const agent = new Agent ( "support" , { instructions: "You are Acme's support agent." , model: "claude-sonnet" , tools: [ tools .memory, tools .files,…from oncell.ai
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