01
Define
Set the goal, operating mode, and boundaries for the run.
Your governed agent operating layer
Give agents goals. Keep the controls.
Plan, supervise, approve, and verify AI work in one focused workspace—with durable memory and evidence at every step.
System health:checking
Workspace overviewOperational
7
Recorded workflow stages
3
Independent worker lanes
Scoped
Tenant-aware operations
Live
Evidence-backed health
Operating loop
From goal to evidence, one connected flow.
Follow the same four stages every time you give the agent meaningful work.
02
Execute
Follow the plan, retrieved context, and governed tool activity.
03
Approve
Pause sensitive actions for an explicit human decision.
04
Verify
Review the result, evidence, and durable memory produced.
Platform capabilities
Designed like an operations desk, not a chatbot.
Agent command center
Start work, inspect progress, and understand the current step.
Durable workflows
Resume long-running work across retries, approvals, and recovery.
Governed tools
Route risky side effects through policy and explicit approval.
Memory and knowledge
Retrieve source-backed context and retain useful outcomes with provenance.
Observability
Trace runtime events, performance, incidents, and worker health.
Release evidence
Verify isolation, security, worker readiness, and evaluation quality.
Product walkthrough
One workspace, shown as one operating story.
01
Command
Describe a bounded outcome and choose how the agent should operate.
02
Workflow
Inspect durable stages, dependencies, tool calls, and progress.
03
Approval
Resolve sensitive actions with the payload and reason visible.
04
Evidence
Review the completed result with verification and provenance.
Governed run
Release review
Workflow
7 stages
Approval
Resolved
Evidence
Verified
Trust and control
Private by design. Observable by default.
Agent work can reach real data and systems, so identity, policy, evidence, and operator decisions remain visible.
Tenant-scoped database access
Connector credentials kept server-side
Risk-based tool approval
Auditable run and decision history
Evaluation-backed release gates
Frequently asked
Clear answers before entering the workspace.
What can Asael do?
It turns a goal into planned, observable work using durable workflows, governed tools, memory, approvals, and stored result evidence.
When does work pause for approval?
Policy pauses actions whose risk requires a human decision before a side effect can reach a connected system.
What information is retained?
Tenant-scoped run events, approvals, results, evidence, and selected memories are retained under the configured policies. Connector secrets remain server-side.
How is release readiness verified?
Evaluation, authentication, tenant-isolation, worker, SLO, and evidence-signing gates are collected into the release report.