Computer Analytics API

Query your organization’s Computer usage analytics programmatically with a free, org-scoped API key

Overview

The Computer Analytics API gives Perplexity Enterprise organizations programmatic access to the same Computer usage analytics shown in the web dashboard — credits, connectors, artifacts, skills, spaces, workflows, and task durations — as bucketed time series you can pull into BI tools or internal reporting.

Analytics requests are free and don’t consume API credits.

This API is available to Perplexity Enterprise organizations. If you don’t see the Analytics API toggle described below, the feature may not be enabled for your organization yet — contact your Perplexity representative.

Getting Access

Access is managed by your organization’s admins from the Perplexity web app:

1. Enable the Analytics API

   In the Perplexity web app, open your organization’s Computer settings and find the Analytics section. Turn on Analytics API to provision API access for your organization.

2. Generate your API key

   In the row that appears below the toggle, select Generate key.

A few properties of analytics API keys:

• Org-scoped, admin-managed — the key belongs to your organization, not to the admin who created it. Any org admin can view the current key and regenerate it.
• One active key — your organization has at most one active analytics key. Regenerating revokes the previous key.
• Analytics-only — the key authenticates analytics endpoints only; it cannot call other Perplexity APIs and has no billing attached.
• Disabling revokes — turning the Analytics API toggle off permanently revokes the key.

Authentication

Pass the key as a bearer token:

curl --request GET \
  --url "https://api.perplexity.ai/v1/analytics/computer/usage?dataset=credit_usage&start_time=1746057600" \
  --header "Authorization: Bearer YOUR_API_KEY"

Querying Usage

GET /v1/analytics/computer/usage returns one time series per request, for a single dataset.

Parameters

Parameter	Required	Description
dataset	Yes	One of credit_usage, connectors, artifacts, skills, spaces, workflows, task_durations.
start_time	Yes	Window start, unix seconds (UTC). Inclusive. Snapped down to the bucket grid.
end_time	No	Window end, unix seconds (UTC). Exclusive. Defaults to now; values in the future are capped at now.
bucket_width	No	1d (default) or 1h. Buckets align to the UTC grid.
limit	No	Buckets per page. 1d: default 7, max 31. 1h: default 24, max 168.
page	No	Opaque pagination cursor from a previous response’s next_page. Valid only with the same query parameters it was issued for.
user_email	No	Restrict results to a single member of your organization. See Filtering by member.

Response

{
  "categories": ["Model", "Credit Source"],
  "data": [
    {
      "start_time": 1746057600,
      "end_time": 1746144000,
      "count": 350,
      "by_categories": {
        "Model": [
          { "category": "claude-opus-4-8", "count": 210 },
          { "category": "claude-sonnet-4-6", "count": 120 }
        ],
        "Credit Source": [
          { "category": "paid", "count": 250 },
          { "category": "promo", "count": 80 }
        ]
      }
    }
  ],
  "has_more": false,
  "next_page": null
}

• categories lists the breakdown axes the dataset surfaces, in canonical render order. Most datasets carry one axis; credit_usage carries two (Model and Credit Source).
• data contains every bucket in the page’s window, in chronological order. Buckets without data carry count: 0 and an empty list under each axis in by_categories.
• by_categories maps each axis label to its breakdown for the bucket. Categories within an axis are the dataset’s dimension values — connector names for connectors, artifact types for artifacts, duration bands for task_durations, paid/promo for credit_usage’s Credit Source, model names for credit_usage’s Model, and the titles your members gave the items for spaces/skills/workflows.
• For credit_usage, count can exceed the sum of any single breakdown — usage without a category attribution counts toward the total but not the breakdown.

Time Windows and Buckets

The API serves complete UTC grid buckets only:

• start_time snaps down to the start of its bucket, so the first bucket can include usage from before your requested start.
• end_time is exclusive and is capped at the current time, then snapped down — the in-progress bucket is never returned. With bucket_width=1d, today’s bucket is not included; use 1h for intraday data.
• A valid window that contains no complete buckets returns 200 with empty data.

Data freshness. The analytics store is synced periodically, not in real time. A count of 0 in a recent bucket can mean the data hasn’t synced yet rather than zero usage. When has_more is false you have reached the current data frontier — poll again later for newer buckets.

Pagination

When the window spans more buckets than limit, the response sets has_more: true and a next_page cursor. Pass it back as page, keeping every other parameter identical — cursors are strictly validated and a cursor used with different parameters returns 400.

import requests

BASE_URL = "https://api.perplexity.ai/v1/analytics/computer/usage"
HEADERS = {"Authorization": "Bearer YOUR_API_KEY"}

params = {
    "dataset": "credit_usage",
    "start_time": 1746057600,
    "bucket_width": "1d",
}

buckets = []
while True:
    response = requests.get(BASE_URL, headers=HEADERS, params=params)
    response.raise_for_status()
    payload = response.json()
    buckets.extend(payload["data"])
    if not payload["has_more"]:
        break
    params["page"] = payload["next_page"]

print(f"Fetched {len(buckets)} buckets")

Filtering by Member

Pass user_email to restrict the series to a single member of your organization:

curl --request GET \
  --url "https://api.perplexity.ai/v1/analytics/computer/usage?dataset=credit_usage&start_time=1746057600&user_email=[e-mail]" \
  --header "Authorization: Bearer YOUR_API_KEY"

The email must belong to a current member of your organization. Any other value — including emails with no Perplexity account — returns the same generic 400:

{
  "error": {
    "message": "user_email does not match a member of this organization.",
    "type": "invalid_request",
    "code": 400
  }
}

Errors

Errors use a consistent envelope:

{
  "error": {
    "message": "Human-readable description.",
    "type": "machine_readable_type",
    "code": 400
  }
}

Status	type	Meaning
400	bad_request	A parameter failed validation (wrong type, malformed value).
400	invalid_request	Parameters are well-formed but semantically invalid — e.g. start_time after end_time, a window over 90 days, a misused pagination cursor, or a user_email that doesn’t match a member.
401	unauthorized	Missing or invalid API key.
404	feature_disabled	The Computer Analytics API is not enabled for your organization.
429	request_rate_limit_exceeded	Rate limit exceeded. Requests are limited per organization across all of its keys; retry with backoff.

Limits

• Time windows are limited to 90 days per request (paginate within the window for long ranges).
• Requests are rate-limited per organization — all keys minted by your org share one allowance.