Best computer use agents
in 2026
A practical guide for evaluating AI agent platforms by architecture, persistence, operational control, and developer readiness.
Computer Agents
Workflow-first cloud agent platform
Best for: Teams shipping repeatable automations and productized agent workflows
- Persistent cloud workspaces and thread continuity
- Scheduling + webhook triggers + API/SDK integration
- Cross-platform operations (web + iOS + macOS)
Perplexity Computer
Answer-first assistant with broad model orchestration
Best for: Users prioritizing research and assistant-style interaction
- Strong research and model-composition experience
- Consumer-grade assistant UX
- Helpful for exploration and synthesis tasks
OpenClaw / openclawd
Self-hosted, local-first agent gateway
Best for: Teams optimizing for infrastructure sovereignty and self-hosting control
- Strong local-first architecture
- High control over runtime and deployment
- Flexible for custom infrastructure policies
Cloud Agent Platforms
Enterprise cloud-native agent stacks
Best for: Cloud-first organizations already deep in hyperscaler ecosystems
- Mature cloud governance and enterprise controls
- Strong integration with existing cloud services
- Scales within existing cloud procurement models
How to choose the right platform
Use this decision framework before committing to an AI agent stack.
Need full workflows, not only responses?
Pick platforms optimized for multi-step execution, task state, and operational continuity, not only single-turn answer quality.
Need persistence?
If workspaces and files must survive between sessions, prioritize persistent runtime architecture over ephemeral task runs.
Need product embedding?
For SaaS teams, SDK/API quality and predictable execution interfaces usually matter more than consumer chat polish.
Need governance and controls?
Define data boundaries, retention/deletion behavior, and operational visibility before scaling agent workflows.
Frequently asked questions
What are computer use agents?
Computer use agents are AI systems that can execute tasks across tools, files, browsers, and APIs, rather than only returning text answers in chat.
What should I evaluate first?
Start with execution reliability, persistence, and operational controls. Then evaluate model quality and UX polish.
Which option is best for building production automations?
Teams often prefer workflow-first platforms with persistent runtimes, scheduling, and SDK/API support because they are easier to operationalize.