List pending policy entries

GET

/api/workspaces/{workspaceId}/policy-entries/pending

• Production

Returns the policies of a workspace that await review: proposals drafted by oHallo (proposed), for example by the learning loop from resolved conversations, and policies created for review (pending_review). Approve or reject each one to decide which rules the assistant applies.

Authorizations

• bearerAuth

Parameters

Path Parameters

workspaceId

required

string format: uuid

The workspace to list pending policies for.

Responses

200

The policies with status pending_review or proposed, newest first. An empty array when nothing awaits review.

List of policy entries.

Array<object>

A policy entry defines a rule that governs how the AI should behave in specific situations. Unlike KB entries (which provide factual answers), policies specify constraints, guardrails, and behavioral guidelines. For example, ‘Never offer more than 10% discount without manager approval’ or ‘Always ask for an order number before looking up shipping status’. Policies can be created manually or proposed by the learning loop.

object

id

required

Unique identifier for the policy entry.

string format: uuid

Example

pe1a2b3c-5678-9abc-def0-1234567890ab

tenantId

required

The tenant this policy belongs to.

string format: uuid

Example

a0b1c2d3-4567-89ab-cdef-0123456789ab

workspaceId

required

The workspace this policy is scoped to.

string format: uuid

Example

w1a2b3c4-5678-9abc-def0-1234567890ab

topic

required

The topic or domain this policy applies to. Used by the AI to determine which policies are relevant to the current conversation.

string

Example

discount_authorization

ruleText

required

The policy rule in natural language. This is the instruction the AI follows.

string

Example

Never offer a discount above 10% without creating an attention item for manager approval. For discounts up to 10%, apply automatically if the customer has placed 3 or more orders.

conditions

Optional structured data stored with the policy, as free-form JSON. The Policy Agent receives it together with the rule text when it retrieves the policy.

object | null

Example

{
  "min_order_value": 500,
  "customer_tier": "gold"
}

sourceType

required

How the policy came to be. manual is a policy written by a person, approved when it is created. extracted is a proposal the learning loop drafted from a resolved conversation. The API stores the value sent, and a policy created with a value other than manual starts as pending_review.

string

Example

manual

confidence

Confidence score between 0 and 1, set by the learning loop when proposing policies. Null for manually created policies.

number | null

Example

0.85

status

required

Where the policy stands, with the values of a knowledge base entry. approved: in use, the assistant applies it. pending_review: created for review, through the API with a sourceType other than manual; it is not applied until it is approved. proposed: drafted by oHallo, for example by the learning loop from a resolved conversation; it is not applied until it is approved, and a proposal that changes an existing policy is applied to that policy when it is approved. rejected: declined in review. archived: no longer in use, kept for the record.

string

Allowed values: pending_review approved rejected archived proposed

Example

approved

createdAt

required

Timestamp when the policy was created.

string format: date-time

Example

2026-02-05T09:00:00.000Z

updatedAt

required

Timestamp when the policy was last updated.

string format: date-time

Example

2026-03-18T11:30:00.000Z