Cursor autocompletes code. Ona multiplies engineering capacity.
Cursor is a VS Code fork with AI autocomplete. It helps one developer in one repo. Ona is an AI engineering platform that runs autonomous agents at fleet scale, inside your VPC.
See what an editor can't do
15-minute walkthrough. No slide deck.
A better editor helps you type. A platform does the work.
Cursor predicts your next edit. Ona runs the next hundred tasks.
Autonomous execution
Ona agents plan, code, test, and open PRs end-to-end. They work in isolated environments while developers focus on architecture and review.
Fleet-scale parallelism
Run hundreds of agents simultaneously across repos. Migrations, CVE patches, and refactors that would take weeks finish in hours.
Your infrastructure
Deploy inside your VPC. Code, secrets, and execution stay in your perimeter. No embeddings on third-party servers.
Editor vs platform
Cursor accelerates individual developers. Ona multiplies organizational capacity.
Ona
CursorAutonomous AI software engineers that plan, code, test, and open PRs. Agents work independently in isolated cloud environments.
VS Code fork with inline completions, chat, and cloud agents. The developer drives every action from the IDE. No autonomous execution.
Inside your VPC. Code, inference, and orchestration never leave your perimeter.
Multi-tenant SaaS. Code embeddings stored on Cursor servers. All inference routed through Cursor's AWS backend. No self-hosted option.
Spin up hundreds of agents on independent VMs. Each works on a separate task, repo, or migration step simultaneously.
Cloud agents run one task per repo. No built-in mechanism for coordinating changes across dozens of repositories or scheduling multi-step workflows.
Agents work end-to-end: read the codebase, make changes, run tests, open PRs. Humans review the output.
Cloud agents can work autonomously on scoped tasks. But the core product is an interactive assistant — the developer accepts, rejects, or edits every suggestion.
Full repository access per environment. Agents can read, build, and test across the entire codebase.
Semantic indexing via cloud embeddings stored on Cursor's servers. Limited to single-repo context. Cannot build, compile, or run tests during suggestions.
Automations span thousands of repos in one coordinated run. Define once, apply everywhere.
Each cloud agent works on one repo at a time. No orchestration layer for org-wide initiatives like migrations or CVE remediation.
Command deny lists and kernel-level security guarantees. Every agent runs in an isolated VM.
Multi-tenant SaaS. Code embeddings stored on Cursor servers. All inference routed through Cursor's AWS backend.
Org guardrails, command deny lists, policy controls. Platform team owns the boundary.
Team-level admin controls for seats and model access. No command-level deny lists, org-wide policy enforcement, or agent action audit trails.
Full experience from any device: review code, monitor agents, approve PRs.
Desktop IDE only. No browser or mobile access to agent workflows.
Declarative devcontainer.json environments. Every agent and developer gets an identical, reproducible setup. No drift.
Cloud agents use environment.json for setup. Local IDE inherits whatever the developer has installed. No org-wide environment standardization.
Enterprises that need fleet-scale automation, org-wide migrations, and autonomous agents inside their security boundary.
Individual developers who want AI autocomplete in their editor. Not built for org-wide automation or multi-repo work.
What it does
Autonomous AI software engineers that plan, code, test, and open PRs. Agents work independently in isolated cloud environments.
VS Code fork with inline completions, chat, and cloud agents. The developer drives every action from the IDE. No autonomous execution.
Where it runs
Inside your VPC. Code, inference, and orchestration never leave your perimeter.
Multi-tenant SaaS. Code embeddings stored on Cursor servers. All inference routed through Cursor's AWS backend. No self-hosted option.
Parallelism
Spin up hundreds of agents on independent VMs. Each works on a separate task, repo, or migration step simultaneously.
Cloud agents run one task per repo. No built-in mechanism for coordinating changes across dozens of repositories or scheduling multi-step workflows.
Autonomy
Agents work end-to-end: read the codebase, make changes, run tests, open PRs. Humans review the output.
Cloud agents can work autonomously on scoped tasks. But the core product is an interactive assistant — the developer accepts, rejects, or edits every suggestion.
Context
Full repository access per environment. Agents can read, build, and test across the entire codebase.
Semantic indexing via cloud embeddings stored on Cursor's servers. Limited to single-repo context. Cannot build, compile, or run tests during suggestions.
Cross-repo scale
Automations span thousands of repos in one coordinated run. Define once, apply everywhere.
Each cloud agent works on one repo at a time. No orchestration layer for org-wide initiatives like migrations or CVE remediation.
Security
Command deny lists and kernel-level security guarantees. Every agent runs in an isolated VM.
Multi-tenant SaaS. Code embeddings stored on Cursor servers. All inference routed through Cursor's AWS backend.
Governance
Org guardrails, command deny lists, policy controls. Platform team owns the boundary.
Team-level admin controls for seats and model access. No command-level deny lists, org-wide policy enforcement, or agent action audit trails.
Mobile access
Full experience from any device: review code, monitor agents, approve PRs.
Desktop IDE only. No browser or mobile access to agent workflows.
Environment consistency
Declarative devcontainer.json environments. Every agent and developer gets an identical, reproducible setup. No drift.
Cloud agents use environment.json for setup. Local IDE inherits whatever the developer has installed. No org-wide environment standardization.
Best for
Enterprises that need fleet-scale automation, org-wide migrations, and autonomous agents inside their security boundary.
Individual developers who want AI autocomplete in their editor. Not built for org-wide automation or multi-repo work.
When a faster editor isn't enough
Cursor accelerates individual developers. These problems need organizational-scale execution.
CVE remediation at scale
Org-wide migrations
Regulated industry compliance
Platform standardization
Cursor edits code. Ona does the work.
A faster editor helps one developer in one repo. An AI engineering platform multiplies the capacity of the entire organization.
VS Code fork with AI autocomplete. Cloud agents limited to one repo at a time. All code context routed through Cursor's servers. No self-hosted option.
AI engineering platform. Autonomous agents that plan, code, test, and ship across hundreds of repos in parallel. Inside your VPC. Full audit trail.
Common questions
Cursor edits code. Ona does the work.
See Ona run a migration, CVE workflow, or code review end-to-end inside your VPC.