Understanding AI Analysis Results from Shilo

When you submit a recording to Shilo, the AI pipeline processes it asynchronously and populates an analysis object with structured coaching data. The same analysis schema is returned for calls, appointments, and roleplays, so the concepts here apply across all three resource types. Understanding how to read and interpret the analysis object is the foundation of any Shilo integration.

Analysis Endpoints

Each recording type exposes a dedicated analysis endpoint:

Resource	Endpoint
Calls	`GET /api/v1/calls/{identifier}/analysis`
Appointments	`GET /api/v1/appointments/{identifier}/analysis`
Roleplays	`GET /api/v1/roleplays/{identifier}/analysis`

The `progress` Field

The progress field is an integer from 0 to 100 that indicates how far along the AI processing pipeline the recording has advanced. Poll the analysis endpoint and check progress before reading any other field:

progress < 100 — Processing is still in progress. Analysis sub-objects may be null or absent. Do not use partial results.
progress == 100 — Processing is complete. All analysis fields are populated and stable.

Store the completed analysis object in your own database after progress reaches 100. This avoids repeated polling on already-processed recordings and reduces unnecessary API calls.

Analysis Sub-Objects

`rating`

The AI’s overall assessment of the call’s quality or outcome.

Field	Type	Description
`outcome`	number	Numeric score representing call quality or result (e.g. `4`)
`reasoning`	string	Human-readable explanation for the score

Example:

{
  "id": "r1r1r1r1-0000-0000-0000-000000000001",
  "outcome": 4,
  "reasoning": "Great rapport and clear value proposition; discovery questions could be more open-ended."
}

`summary`

A concise natural-language narrative of what happened on the call.

Field	Type	Description
`outcome.summary`	string	Human-readable summary of the conversation

Example:

{
  "id": "s1s1s1s1-0000-0000-0000-000000000002",
  "outcome": {
    "summary": "Prospect expressed interest in the property and agreed to a follow-up appointment next Thursday."
  }
}

`coaching`

Structured coaching feedback broken into two complementary lists.

Field	Type	Description
`possible_improvements`	string[]	Specific behaviors the agent can improve on future calls
`top_moments`	string[]	Positive highlights worth reinforcing

Example:

{
  "id": "c1c1c1c1-0000-0000-0000-000000000003",
  "possible_improvements": [
    "Ask more open-ended discovery questions before presenting price",
    "Acknowledge objections before pivoting to benefits"
  ],
  "top_moments": [
    "Handled the timeline objection with a compelling urgency frame",
    "Confirmed next steps clearly at the end of the call"
  ]
}

`disposition`

The AI’s classification of how the call ended or what outcome it represents.

Field	Type	Description
`outcomes`	string[]	One or more disposition labels (e.g. `"Qualified lead"`)
`reasoning`	string	Explanation of why the call was classified this way

Example:

{
  "id": "d1d1d1d1-0000-0000-0000-000000000004",
  "outcomes": ["Qualified lead"],
  "reasoning": "Prospect confirmed budget and expressed positive intent to move forward."
}

`objections`

Objections that the prospect raised during the conversation.

Field	Type	Description
`outcomes`	string[]	List of identified objection strings

Example:

{
  "id": "o1o1o1o1-0000-0000-0000-000000000005",
  "outcomes": ["Price concerns", "Needs to consult spouse"]
}

`action_items`

Follow-up tasks identified from the call, split into two priority tiers.

Field	Type	Description
`primary`	string[]	High-priority actions the agent should take immediately
`secondary`	string[]	Supporting or lower-priority follow-up tasks

Example:

{
  "id": "ai1ai1a1-0000-0000-0000-000000000006",
  "primary": ["Schedule follow-up appointment for next Thursday"],
  "secondary": ["Send recap email with listing details"]
}

`speakers`

AI-resolved speaker identities reconciled with your user and contact data.

Field	Type	Description
`user_name`	string	Resolved name of the agent on the call
`client_name`	string	Resolved name of the client or prospect

Example:

{
  "id": "sp1sp1s1-0000-0000-0000-000000000007",
  "user_name": "Alex Johnson",
  "client_name": "Jamie Rivera"
}

Complete Analysis Response Example

{
  "id": "a1b2c3d4-0000-0000-0000-111122223333",
  "recording_id": "ee6f2136-b94a-4438-9335-3acf5b2a0d31",
  "created_at": "2030-09-24T12:34:56Z",
  "progress": 100,
  "rating": {
    "id": "r1r1r1r1-0000-0000-0000-000000000001",
    "outcome": 4,
    "reasoning": "Great rapport and clear value proposition; discovery questions could be more open-ended."
  },
  "summary": {
    "id": "s1s1s1s1-0000-0000-0000-000000000002",
    "outcome": {
      "summary": "Prospect expressed interest in the property and agreed to a follow-up appointment next Thursday."
    }
  },
  "coaching": {
    "id": "c1c1c1c1-0000-0000-0000-000000000003",
    "possible_improvements": [
      "Ask more open-ended discovery questions before presenting price"
    ],
    "top_moments": [
      "Confirmed next steps clearly at the end of the call"
    ]
  },
  "disposition": {
    "id": "d1d1d1d1-0000-0000-0000-000000000004",
    "outcomes": ["Qualified lead"],
    "reasoning": "Prospect confirmed budget and expressed positive intent to move forward."
  },
  "objections": {
    "id": "o1o1o1o1-0000-0000-0000-000000000005",
    "outcomes": ["Price concerns", "Needs to consult spouse"]
  },
  "action_items": {
    "id": "ai1ai1a1-0000-0000-0000-000000000006",
    "primary": ["Schedule follow-up appointment for next Thursday"],
    "secondary": ["Send recap email with listing details"]
  },
  "speakers": {
    "id": "sp1sp1s1-0000-0000-0000-000000000007",
    "user_name": "Alex Johnson",
    "client_name": "Jamie Rivera"
  }
}

Transcripts

In addition to the structured analysis object, you can retrieve the full call transcript with AI-resolved speaker names:

Resource	Endpoint
Calls	`GET /api/v1/calls/{identifier}/transcript`
Appointments	`GET /api/v1/appointments/{identifier}/transcript`
Roleplays	`GET /api/v1/roleplays/{identifier}/transcript`

A 409 Conflict response means the transcript is not yet ready—speaker resolution must complete before the transcript is available. Poll and retry after a short wait.

The transcript endpoint is not supported for Shilo accounts connected to Follow Up Boss. Calling it from such an account returns 403 Forbidden.

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Core Concepts

Guides

Understanding AI Analysis Results from Shilo

Analysis Endpoints

The `progress` Field

Analysis Sub-Objects

`rating`

`summary`

`coaching`

`disposition`

`objections`

`action_items`

`speakers`

Complete Analysis Response Example

Transcripts

​Analysis Endpoints

​The progress Field

​Analysis Sub-Objects

​rating

​summary

​coaching

​disposition

​objections

​action_items

​speakers

​Complete Analysis Response Example

​Transcripts

Analysis Endpoints

The `progress` Field

Analysis Sub-Objects

`rating`

`summary`

`coaching`

`disposition`

`objections`

`action_items`

`speakers`

Complete Analysis Response Example

Transcripts