Agents prepare
Gather context
Prepare the action
Specialists gather context, check records, compare options, and prepare the next action.
AI & governance
AI that moves the work. People who keep the authority.
ProcureVerse agents prepare, analyze, and route procurement work while policy and human checkpoints protect the decisions that carry risk, commitment, or financial impact.
The control model
One clear path from machine work to accountable action.
The agent does the operational preparation. Policy determines the boundary. The right person makes the sensitive decision, and the evidence stays with the work.
Start
Policy checks
Check authority
Test risk & data
Permissions, thresholds, risk rules, and data quality determine what can move forward.
People decide
Approve or reject
Escalate or override
Authorized reviewers retain control over commitments, exceptions, changes, and release.
Evidence remains
Record the decision
Preserve the trail
Inputs, recommendations, approvals, overrides, and outcomes stay attached to the record.
Accountable action
The same governance workflow applies wherever a sensitive decision appears.
Configurable autonomy
Choose how far each agent can go.
Autonomy can increase with policy, evidence, and data quality. Sensitive actions keep a hard human floor regardless of automation level.
- L0AssistMonitor work and bring forward what needs attention.
- L1RecommendExplain a suggested action for a person to review.
- L2Prepare & waitCreate the draft and route it to the right approver.
- L3Act & reportExecute only within configured policy boundaries.
app.procureverse.ai/settings/ai/autonomy-dial
Human-control floor
Contract signature
Payment release
Sanctions override
Supplier bank-detail change
app.procureverse.ai/agents/accountability
Accountability by design
Review what happened. See who overruled it.
Agent activity is tied back to the record, recommendation, policy boundary, and human response. Reviewers can inspect the decision without reconstructing it from inboxes and spreadsheets.
- The source and linked procurement records
- The recommendation and policy checks used
- The person, role, and time behind each decision
- Overrides, exceptions, and the resulting action
Safeguards in operation
Controls apply before an exception becomes an incident.
Policy, review, data quality, and pause controls meet at the point of action. Every safeguard has a defined trigger, owner, and response.
Hard floors
High-impact actions cannot be pushed beyond their required human checkpoint.
Authority ceilingHuman approval
L0
L1
L2
L3
Sensitive action stops at L2
Four-eyes changes
Material policy changes require a second authorized reviewer before they take effect.
Policy change review
JL
AR
Two authorized reviewers recorded
Data-quality ceiling
Missing, stale, or conflicting data lowers how far an agent is allowed to proceed.
Required inputs
Autonomy loweredSupplier dataComplete
Bank detailsConflict
Policy matchVerified
Kill switch
Pause agent work at a safe checkpoint and route anything in flight to a human queue.
Agent operations
Execution paused
Work preserved
Routed to human queue
Start safely
Earn autonomy with evidence.
Start in a safe operating mode, confirm the evidence with your team, then widen authority only where policy and data support it.
Dry run
Use fixed sample cases without changing operational records.
Review
Validate recommendations, evidence, and approval routing with your team.
Expand
Increase authority only where policy and data support it.
Make governance concrete
See where agents assist, where people decide, and what evidence remains.
Bring a real purchasing scenario and your approval model. We will map the agent boundaries, human checkpoints, and audit evidence to your workflow.