Retrieve and Interpret AI Call Analysis from Shilo

Once you submit a recording to Shilo, the AI pipeline processes it asynchronously. Retrieving analysis requires polling the appropriate endpoint until the progress field reaches 100, then reading the structured result. This guide covers the polling pattern, every analysis field, and how to retrieve the full call transcript.

Analysis Endpoints

All three recording types expose identical analysis and transcript endpoints:

Resource	Analysis endpoint	Transcript endpoint
Calls	`GET /api/v1/calls/{identifier}/analysis`	`GET /api/v1/calls/{identifier}/transcript`
Appointments	`GET /api/v1/appointments/{identifier}/analysis`	`GET /api/v1/appointments/{identifier}/transcript`
Roleplays	`GET /api/v1/roleplays/{identifier}/analysis`	`GET /api/v1/roleplays/{identifier}/transcript`

Choosing Your Identifier

Right after submitting a call, use the call_event_id from the 202 response as your identifier:

call_event_id:ee6f2136-b94a-4438-9335-3acf5b2a0d31

Once analysis completes and you have retrieved the full call object (which contains the stable Shilo id), you can switch to the plain UUID for any subsequent lookups. You can also use external_recording_id:{your-recording-id} at any time if you prefer to reference calls by your own IDs.

Polling Until Complete

The progress field in the analysis response is an integer from 0 to 100. Keep polling until it equals 100.

curl https://api.shilo.ai/api/v1/calls/call_event_id:ee6f2136-b94a-4438-9335-3acf5b2a0d31/analysis \
  -H "x-api-key: YOUR_API_KEY"

While processing (progress < 100):

{
  "id": "a1b2c3d4-0000-0000-0000-111122223333",
  "recording_id": "ee6f2136-b94a-4438-9335-3acf5b2a0d31",
  "created_at": "2030-09-24T12:34:56Z",
  "progress": 60
}

When complete (progress == 100), all sub-objects are populated.

Use exponential backoff when polling. Start with a 5-second interval, then double it on each unsuccessful poll up to a maximum of 60 seconds. Most calls complete within a few seconds to a few minutes depending on recording length.

Analysis Fields

`rating`

The AI’s numeric assessment of the call quality.

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

outcome (number) — Numeric score representing overall call quality or outcome result
reasoning (string) — Human-readable explanation of the score

`summary`

A concise narrative of the call.

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

outcome.summary (string) — Natural-language summary of the conversation

`coaching`

Structured coaching feedback for the agent.

"coaching": {
  "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"
  ]
}

possible_improvements (string[]) — Specific behaviors to work on in future calls
top_moments (string[]) — Positive highlights worth reinforcing in coaching sessions

`disposition`

The AI’s classification of the call outcome.

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

outcomes (string[]) — One or more outcome labels for the call
reasoning (string) — Explanation for the classification

`objections`

Objections the prospect raised during the conversation.

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

outcomes (string[]) — List of objection strings identified by the AI

`action_items`

Follow-up tasks extracted from the call, split by priority.

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

primary (string[]) — High-priority tasks the agent should act on immediately
secondary (string[]) — Supporting or lower-priority follow-up actions

`speakers`

AI-resolved speaker identities.

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

user_name (string) — Resolved name of the agent, reconciled against your user data
client_name (string) — Resolved name of the client or prospect

Complete Example Response

{
  "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": "Strong 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",
      "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": {
    "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"
  }
}

Retrieving the Transcript

Once speaker resolution is complete, you can retrieve the full sanitized transcript with AI-resolved speaker labels:

curl https://api.shilo.ai/api/v1/calls/call_event_id:ee6f2136-b94a-4438-9335-3acf5b2a0d31/transcript \
  -H "x-api-key: YOUR_API_KEY"

If the transcript is not yet ready, you receive a 409 Conflict response. Wait a moment and retry.

The transcript endpoint is not supported for accounts connected to Follow Up Boss. Calling it from such an account returns 403 Forbidden with a message indicating the CRM integration limitation.

The transcript endpoint for roleplays does not carry the Follow Up Boss restriction—GET /api/v1/roleplays/{identifier}/transcript works for all account types.

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Core Concepts

Guides

Retrieve and Interpret AI Call Analysis from Shilo

Analysis Endpoints

Choosing Your Identifier

Polling Until Complete

Analysis Fields

`rating`

`summary`

`coaching`

`disposition`

`objections`

`action_items`

`speakers`

Complete Example Response

Retrieving the Transcript

​Analysis Endpoints

​Choosing Your Identifier

​Polling Until Complete

​Analysis Fields

​rating

​summary

​coaching

​disposition

​objections

​action_items

​speakers

​Complete Example Response

​Retrieving the Transcript

Analysis Endpoints

Choosing Your Identifier

Polling Until Complete

Analysis Fields

`rating`

`summary`

`coaching`

`disposition`

`objections`

`action_items`

`speakers`

Complete Example Response

Retrieving the Transcript