Give every agent its own cloud computer, give your team one place to review the work, and keep source, secrets, and runtime on infrastructure you control.
Run agent sandboxes on a provider and in a region you control.
Agents receive placeholders; values are substituted outside the model.
One disposable cloud computer per agent session, never shared.
Every command, preview, and pull request stays attached to its session.
Uno does not ship one general-purpose assistant. Each workspace comes with six built-in profiles that carry their own instructions, permissions, and output format — so the agent that investigates is not the agent that changes your code, and the agent that verifies a release is not the one that built it.
Answers questions across repositories and connected sources, then routes the actual deliverable to the right agent instead of doing the work itself.
Onboarding at speed: ask how a service really works, then hand the follow-up straight to a specialist.
Implements assigned tasks, writes regression tests, runs browser verification where it matters, and delivers through your existing pull request workflow.
Parallel delivery: a queue of scoped tickets becomes a set of tested, reviewable pull requests.
Reproduces a bug, establishes a root cause from code and runtime evidence, and publishes a report with an implementation-ready task graph it never executes itself.
Triage without a war room: reproduction, cause, and an approval-ready fix plan attached to the incident.
Inspects code, dependency manifests, and lockfiles against authoritative advisories, then separates confirmed issues from theoretical exposure using your actual versions and reachable code.
Routine dependency review: advisory noise reduced to the findings that touch code you actually run.
Looks at maintainability, duplication, type safety, flaky tests, and testing gaps, and proposes improvements to the prompts, rules, and skills your agents share.
Compounding quality: the lessons from last week's sessions become workspace rules every agent inherits.
Turns a brief into a specification with success criteria and a dependency-ordered task graph, verifies finished work in a separate session, and coordinates releases.
Traceability from brief to release: a plan humans approve, then QA that never grades its own homework.
Profiles hand work to each other through workspace tasks, and a person stays in the loop at each hand-off. Investigation, implementation, and verification stay separate, which is what makes the throughput reviewable.
Oncall reproduces and publishes a root-cause report. A human approves its task graph, Engineering implements and tests it, and Product verifies the result in a separate session.
Product turns a brief into ordered Engineering tasks. Each task starts its own session on its own cloud computer, so ten agents can work without colliding over branches or ports.
Security audits dependencies and reachable code, separates confirmed issues from noise, and hands the remediation to Engineering with the evidence still attached.
Chief answers architecture questions straight from the repositories, and Code Intelligence turns the recurring gaps into rules and skills every future session inherits.
Most agent pilots stall at the security review, not at the demo. Uno is built so the parts that matter — where code is checked out, where commands run, and where credentials are resolved — stay under your control.
The sandbox runtime is provider-pluggable. Checkouts, builds, tests, and the agent desktop can execute on infrastructure and in regions you nominate, so your source never has to leave your environment to be worked on.
Every session gets its own VM with its own branch, dependencies, ports, and runtime state. Nothing is shared between sessions, and tearing a sandbox down removes its credentials with it.
Sensitive workspace values are registered with the runtime's secret service. Agents only ever see opaque placeholders, substituted into outbound requests outside the sandbox and only for hosts you allow-list.
Agents reach only the repositories you attach through your own GitHub installation, on the branches you choose. Delivery defaults to a pull request; merging and deploying stay human decisions.
Choose the model provider and model your workspace uses, so inference follows the same procurement and data-processing agreements as the rest of your stack.
Prompts, tool calls, commands, runtime state, published previews, and the resulting pull request stay recorded against the session, with workspace roles deciding who can change what.
Policy lives in the workspace, not in each person's prompt. Change it once and the next session everyone starts already follows it.
Encode your standards once as workspace rules and shared skills; every agent loads them before it touches a repository.
Pin the image, packages, and setup commands a sandbox starts from, so a session is reproducible rather than improvised.
Connect workspace MCP servers so agents can reach your issue tracker, observability, and internal services under the same policy.
Tell us about your repositories, your review process, and where your code is allowed to run. We will walk through deployment options, the six agent profiles, and what a pilot looks like on your infrastructure.