Where does the work live?
Compare private deployment, persistent runtimes, files, tools, browser access, and company-controlled context.
AI agent platform comparisons
The AI agent market is crowded. Let's make it legible.
Pick a platform, open the scorecard, and compare the ten capabilities that determine whether an agent can become part of a real operating team—not just complete an impressive demo.
One scorecard, ten questions
Look past the chatbot
Every comparison checks the same operating layers, with ✓ for native, ◐ for partial, — for absent, and ? where first-party material does not verify the claim.
Who stays in control?
Check identity, permissions, schedules, approvals, escalation, releases, run evidence, and recovery.
Can it become a team?
Look for shared rooms, durable context, specialist handoffs, external agents, reuse, and observability.
Personal and general-purpose agents
Great at getting things done. But whose operating system is it?
Start here when you are comparing Bewize with personal assistants, super agents, and model-vendor workspaces.
Always-on personal agent
OpenAI Dots
Persistent OpenAI-managed work versus a company-owned agent team.
Open scorecard →Dedicated secure VM
Meta Muse
Personal delegation versus shared, governed company operations.
Open scorecard →Google-native agent
Gemini Spark
A proactive personal agent versus an open operating team.
Open scorecard →Enterprise assistant
ChatGPT Enterprise
One managed cloud assistant versus a company-controlled fleet.
Open scorecard →Enterprise assistant
Claude Enterprise
Strong knowledge work versus persistent multi-agent operations.
Open scorecard →General agent
Manus
Broad task completion versus recurring company-owned workflows.
Open scorecard →Super agent
Genspark
All-in-one output generation versus durable operating capacity.
Open scorecard →Cloud AI teammate
Grok Bot
Cloud-native teammates versus private agent infrastructure.
Open scorecard →Enterprise platforms and control planes
The heavyweight division
These platforms overlap with Bewize on governance, orchestration, enterprise context, or private deployment. The interesting differences live at the boundaries.
Identity and governance
Microsoft Agent 365
Microsoft ecosystem control versus an integrated private operating environment.
See the matchup →Workflow suite
ServiceNow AI Platform
ServiceNow-centered work versus an independent AI workforce.
See the matchup →Cloud infrastructure
Amazon Bedrock AgentCore
AWS building blocks versus a ready human-and-agent operating model.
See the matchup →CRM-centered agents
Salesforce Agentforce 360
Native Salesforce depth versus company-wide cross-system work.
See the matchup →Enterprise knowledge
Glean Agents
Knowledge-graph strength versus company-operated runtimes and rooms.
See the matchup →Collaborative workspace
Dust
A close team-workspace comparison with a different deployment boundary.
See the matchup →Agent factory
StackAI
Visual agent building versus persistent human-agent operating rooms.
See the matchup →Enterprise orchestration
IBM watsonx Orchestrate
A broad enterprise stack versus a focused, adaptable operating boundary.
See the matchup →Developer platform
Cloudflare Agents
Edge-native agent infrastructure versus a managed organizational fleet.
See the matchup →Open-source control plane
OpenClaw Enterprise
Extensible self-hosting versus managed operations plus shared rooms.
See the matchup →No mystery checkmarks
Competitor marks come from cited first-party material. If a capability is unclear, the page says ? not verified instead of guessing. Product boundaries change, so decisive requirements should still be demonstrated in a live evaluation.Compare your real workflow
Bring the systems, people, approvals, and exceptions involved. We will demonstrate the corresponding Bewize operating model.
Architecture conversation
Tell us what your team needs to control
Share your deployment boundary, number of agents, work surfaces, and governance requirements. We will reply by email to arrange a focused technical discussion.
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