GET /analyses/:analysisId

Endpoint

GET /v1/analyses/{analysisId}

Request

curl -X GET "http://client-omni-api.argosidentity.com/v1/analyses/{analysisId}?waitForReport=true&timeoutSeconds=120" \
  -H "x-api-key: your-api-key-here"

Query Parameters

Parameter	Type	Required	Default	Description
`waitForReport`	`boolean`		`false`	Wait for report generation (long polling)
`timeoutSeconds`	`number`		`120`	Max wait time in seconds (10–300)

When waitForReport is set to true, the request will hold the connection open until the report is generated or the timeoutSeconds threshold is reached. This is useful for synchronous workflows where you need the report immediately after analysis completes.

Response Structure

The analysis response has a fixed skeleton (top-level fields, risk assessment, system metadata, findings, etc.) that is always present regardless of your workflow configuration.

The extractedData and outputSchema sections are determined by your workflow’s output schema configuration. The fields inside them change depending on how you defined your output schema. The example below shows a KYB verification workflow — your results will have different fields based on your own schema.

Top-Level Fields

These fields are always present in every analysis response.

string

required

Unique analysis ID (analysis_ prefix)

profileId

string

required

Profile ID this analysis belongs to

folderId

string | null

required

Target folder ID (null for full-profile analysis)

engineId

string | null

required

Engine ID used (null when using default engine)

playbookId

string

required

Playbook ID used for the analysis (PB- prefix)

engine

object | null

required

Engine details (null when using default engine)

status

string

required

Analysis status: pending / processing / completed / failed

processingTimeMs

number

required

Processing time in milliseconds

verificationStatus

string

required

Final verification status: pending_review / approved / rejected

error

string | null

required

Error message (null on success)

options

object | null

Options passed when the analysis was requested

clientMetadata

object | null

Client metadata passed when the analysis was requested

primaryReportId

string | null

Primary report ID generated for this analysis (rpt_ prefix)

requestedAt

string

required

Analysis request time (ISO 8601)

completedAt

string | null

required

Analysis completion time (ISO 8601, null if not completed)

createdAt

string

required

Record creation time (ISO 8601)

`riskAssessment` — Risk Assessment

Final risk assessment computed by the AI agent after all verification steps.

Field	Type	Description
`riskLevel`	`string`	Risk level: `low` / `medium` / `high`
`riskScore`	`number`	Risk score (0–100, higher = riskier)
`riskFactors`	`string[]`	List of factors contributing to the risk level

`systemMetadata` — Execution Metadata

Internal execution information from the AI agent during analysis.

Field	Type	Description
`totalIterations`	`number`	Total iterations performed by the agent
`completedWorkIds`	`number[]`	IDs of successfully completed work items
`workflowHistory`	`object[]`	Execution summary for each work item

`systemMetadata.workflowHistory[]`

Field	Type	Description
`workId`	`number`	Work sequence number (starts at 1)
`actionName`	`string`	Executed action function name
`query`	`string`	Query/instruction used by the agent
`reason`	`string`	Agent’s reasoning for the result
`success`	`boolean`	Whether the work succeeded
`iteration`	`number`	Iteration number when completed
`timestamp`	`string`	Completion time (ISO 8601)

`extractedData` — Extracted Structured Data

This section is dynamic. The fields inside extractedData are determined by the output schema you defined in your workflow. The example below is from a KYB workflow with business registration verification — your fields will differ.

The AI extracts data from documents and structures it according to your output schema. The following sub-sections are common patterns:

`extractedData.review_result` — Final Review Result

Field	Type	Description
`final_action`	`string`	Final action: `approve` / `reject` / `manual_review`
`final_risk_level`	`string`	Final risk level: `low` / `medium` / `high`
`final_action_reason`	`string`	Reasoning for the final action
`final_risk_level_reason`	`string`	Reasoning for the final risk level

`extractedData.extracted_values` — Raw Extracted Values

Values extracted directly from submitted documents. The fields depend on your output schema definition. Example (KYB with business registration):

Field	Type	Description
`brc_business_name`	`string`	Company name from business registration certificate
`brc_business_registration_number`	`string`	Business registration number
`brc_corporate_registration_number`	`string`	Corporate registration number
`brc_representative_name`	`string`	Representative name
`brc_address`	`string`	Business address
`brc_opening_date`	`string`	Opening date
`brc_issue_date`	`string`	Issue date

`extractedData.category_judgements` — Verification Judgements

Per-category verification results with pass/fail status and reasoning.

Field	Type	Description
`{field}_check_result`	`string`	Check result: `pass` / `fail` / `unverifiable` / `needs_review`
`{field}_check_reason`	`string`	Reasoning for the check result
`overall_consistency_result`	`string`	Overall consistency: `pass` / `needs_review` / `fail`
`overall_consistency_reason`	`string`	Reasoning for overall consistency

`extractedData.document_validations` — Document Validity

Field	Type	Description
`{document}_is_valid`	`boolean`	Whether the document is valid
`{document}_is_valid_reason`	`string`	Reasoning for validity check

`outputSchema` — Enriched Output Schema

Contains the same data as extractedData, structured as your workflow’s JSON Schema with actual values filled in. Use extractedData as the canonical field.

Common fields in `outputSchema.properties`

Field	Type	Description
`request_id`	`string`	Request identifier (same as profile ID)
`policy_flags`	`string[]`	Policy violation/caution flags
`review_result`	`object`	Final review result
`extracted_values`	`object`	Raw extracted values from documents
`category_judgements`	`object`	Per-category verification judgements
`document_validations`	`object`	Document validity results
`recommended_next_steps`	`string[]`	AI-recommended follow-up actions

`extractionStatus` — Field Extraction Status

Status map indicating whether each top-level output schema field was successfully extracted.

Value	Meaning
`"extracted"`	Field was successfully extracted/generated
`"missing"`	Field extraction failed (no document or information)

`rawActionResults` — Raw Action Results

Raw result data returned by each AI action. Keys are actionName.

Field	Type	Description
`answer`	`string`	Action result text (RAG response or LLM output)
`workId`	`number`	Work sequence number
`citationsCount`	`number`	Number of citation chunks used
`verificationStatus`	`string`	Verification result: `passed` / `needs_review` / `failed`

`agentAuditLog[]` — Agent Audit Log

Detailed execution log of every step the AI agent performed. More granular than rawActionResults, includes MCP tool call details.

Field	Type	Description
`workId`	`number`	Work sequence number
`actionName`	`string`	Action name
`category`	`string`	Action category. Examples include `Document Classification`, `Data Extraction`, `Format Validation`, `Status Validation`, `Data Consistency`, `Document Processing`, and `mcp` (external tools). Actual values depend on the workflow policy.
`query`	`string`	Query or instruction sent by the agent
`reasoning`	`string`	Agent’s reasoning (may be empty)
`success`	`boolean`	Whether execution succeeded
`iteration`	`number`	Iteration number
`durationMs`	`number`	Execution duration in milliseconds
`executedAt`	`string`	Execution time (ISO 8601)
`verificationStatus`	`string	null`	Per-step verification outcome when applicable (e.g., `passed` / `needs_review` / `failed`). May be omitted for steps that do not produce a pass/fail (such as some MCP-only actions).
`targetItemIds`	`string[]`	Item IDs referenced by this action
`ragResponse`	`object	null`	RAG query result (if applicable)
`mcpToolCalls`	`object[]	null`	MCP tool call details (if applicable)

`agentAuditLog[].ragResponse`

Present only for actions that performed RAG queries.

Field	Type	Description
`answer`	`string`	RAG-generated response text
`citations`	`object[]`	Citation chunks used in the response
`chunksSearched`	`number`	Number of chunks searched
`processingTimeMs`	`number`	RAG processing time in milliseconds

`agentAuditLog[].mcpToolCalls[]`

Present only for actions that called MCP external tools (e.g., AML screening).

Field	Type	Description
`toolName`	`string`	MCP tool name (e.g., `search_individual`)
`engineCode`	`string`	Engine identifier for this tool (e.g., `aml-search`)
`engineName`	`string`	Display name of the engine (e.g., `AML Search - Person`)
`params`	`object`	Tool call parameters
`success`	`boolean`	Whether the call succeeded
`startedAt`	`string`	Call start time (ISO 8601)
`executionTimeMs`	`number`	Tool call duration in milliseconds
`rawContent`	`object`	Raw response data from the tool
`fallbackToRag`	`boolean`	Whether RAG fallback was triggered on failure
`selectionReason`	`string`	Agent’s reason for selecting this tool

`findings[]` — Verification Findings

Sorted summary of each action’s result. Designed for UI display.

Field	Type	Description
`id`	`string`	Finding ID (`af_` prefix)
`category`	`string`	Category (same as action name)
`result`	`string`	Result: `passed` / `warning` / `failed`
`details`	`string`	Result details (may be truncated)
`sortOrder`	`number`	Display order

`recommendations[]` — Recommendations

System-generated follow-up action recommendations.

Field	Type	Description
`id`	`string`	Recommendation ID (`ar_` prefix)
`content`	`string`	Recommendation content
`priority`	`number`	Priority (lower = higher priority)
`sortOrder`	`number`	Display order

`targetItems[]` — Target Items

Items referenced in this analysis.

Field	Type	Description
`itemId`	`string`	Item ID (`item_` prefix)
`name`	`string`	Item name
`type`	`string`	Item type: `file` / `text` / `json`
`sourceRef`	`string	null`	Source reference info

Status Enums

Analysis Status
Verification Status
Risk Level
Finding Result
Check Result

Value	Description
`pending`	Awaiting analysis
`processing`	Analysis in progress
`completed`	Analysis complete
`failed`	Analysis failed

Value	Description
`pending_review`	Manual review required
`approved`	Approved
`rejected`	Rejected

Value	Description
`low`	Low risk
`medium`	Medium risk
`high`	High risk

Value	Description
`passed`	Passed
`warning`	Warning (review needed)
`failed`	Failed

Value	Description
`pass`	Match confirmed
`fail`	Mismatch
`unverifiable`	Cannot verify (document missing)
`needs_review`	Further review needed

Overview

API Reference

Endpoint

Request

Query Parameters

Response Structure

Top-Level Fields

`riskAssessment` — Risk Assessment

`systemMetadata` — Execution Metadata

`systemMetadata.workflowHistory[]`

`extractedData` — Extracted Structured Data

`extractedData.review_result` — Final Review Result

`extractedData.extracted_values` — Raw Extracted Values

`extractedData.category_judgements` — Verification Judgements

`extractedData.document_validations` — Document Validity

`outputSchema` — Enriched Output Schema

Common fields in `outputSchema.properties`

`extractionStatus` — Field Extraction Status

`rawActionResults` — Raw Action Results

`agentAuditLog[]` — Agent Audit Log

`agentAuditLog[].ragResponse`

`agentAuditLog[].mcpToolCalls[]`

`findings[]` — Verification Findings

`recommendations[]` — Recommendations

`targetItems[]` — Target Items

Status Enums

Overview

API Reference

​Endpoint

​Request

​Query Parameters

​Response Structure

​Top-Level Fields

​riskAssessment — Risk Assessment

​systemMetadata — Execution Metadata

​systemMetadata.workflowHistory[]

​extractedData — Extracted Structured Data

​extractedData.review_result — Final Review Result

​extractedData.extracted_values — Raw Extracted Values

​extractedData.category_judgements — Verification Judgements

​extractedData.document_validations — Document Validity

​outputSchema — Enriched Output Schema

​Common fields in outputSchema.properties

​extractionStatus — Field Extraction Status

​rawActionResults — Raw Action Results

​agentAuditLog[] — Agent Audit Log

​agentAuditLog[].ragResponse

​agentAuditLog[].mcpToolCalls[]

​findings[] — Verification Findings

​recommendations[] — Recommendations

​targetItems[] — Target Items

​Status Enums

Endpoint

Request

Query Parameters

Response Structure

Top-Level Fields

`riskAssessment` — Risk Assessment

`systemMetadata` — Execution Metadata

`systemMetadata.workflowHistory[]`

`extractedData` — Extracted Structured Data

`extractedData.review_result` — Final Review Result

`extractedData.extracted_values` — Raw Extracted Values

`extractedData.category_judgements` — Verification Judgements

`extractedData.document_validations` — Document Validity

`outputSchema` — Enriched Output Schema

Common fields in `outputSchema.properties`

`extractionStatus` — Field Extraction Status

`rawActionResults` — Raw Action Results

`agentAuditLog[]` — Agent Audit Log

`agentAuditLog[].ragResponse`

`agentAuditLog[].mcpToolCalls[]`

`findings[]` — Verification Findings

`recommendations[]` — Recommendations

`targetItems[]` — Target Items

Status Enums