Daily Data Export API

The Daily Data Export API returns presigned download URLs for an AI Employee's Agent QA daily export and its manifest file. The export is generated nightly by Ema's internal workflow and covers all calls processed on the specified UTC date.

Use this API to pull evaluation results, scorecards, and insights into your own data warehouse, BI tool, or downstream analytics system.

13.1 Authentication & Headers

13.2 Get Daily Export Data

Query Parameters

Example Request

curl -X GET \
  "{base_url}/api/agent-qa/get_daily_data?persona_id=<persona_id>&date=2025-06-01" \
  -H "Authorization: Bearer <token>"

Response

A successful response (200 OK) returns a JSON object with the following fields:

13.3 File Structure

The two presigned URLs point to files stored in Ema's internal cloud storage. One is a data file containing the actual records and results. The other is a manifest file describing the export partition. URLs expire within an hour; re-request if needed.

Data File (signed_url → agent_qa_export.jsonl)

The data file is JSONL (newline-delimited JSON). Each line is a self-contained JSON object representing one processed call record, corresponding to a single resource_id. The schema is defined by AgentQACallRecord.

Insight Attributes

Rule Result Attributes

Manifest File (manifest_signed_url → manifest.json)

The manifest file is a single JSON object describing the export partition. It is written alongside the data file after the nightly export completes successfully. The schema is defined by AgentQAExportManifest.

13.4 Error Codes

13.5 Rate Limits

A rate limit of 1 query per second is enforced on this API.

13.6 Sample Python

The snippet below downloads and parses agent_qa_export.jsonl from the presigned URL returned by the API.

import json
import urllib.request

# Step 1 — call the API to get the presigned URLs
req = urllib.request.Request(
    "https://api.<region>.ema.co/api/agent-qa/get_daily_data"
    "?persona_id=<persona_id>&date=2025-06-01",
    headers={
        "Authorization": "Bearer <token>",
        "x-persona-id": "<persona_id>",
    },
)
with urllib.request.urlopen(req) as resp:
    urls = json.load(resp)

signed_url = urls["signed_url"]
manifest_signed_url = urls["manifest_signed_url"]

# Step 2 — download and parse the JSONL data file
records = []
with urllib.request.urlopen(signed_url) as resp:
    for line in resp:
        line = line.strip()
        if line:
            records.append(json.loads(line))

# Step 3 — work with the records
for record in records:
    resource_id  = record["resource_id"]
    agent_id     = record["agent_id"]
    final_score  = record.get("final_score")
    sentiment    = record.get("sentiment")
    resolution   = record.get("resolution_status")
    rule_results = record["rule_results"]
    insights     = record["insights"]

    print(f"{resource_id} | agent={agent_id} | score={final_score} | {sentiment} | {resolution}")

    for rule in rule_results:
        print(f"  [{rule['result']}] {rule['rule_name']} (weight={rule['rule_weight']})")

    for insight in insights:
        print(f"  [{insight['insight_type']}] {insight['driver']} — {insight['category']}")

# Step 4 — download and parse the manifest
with urllib.request.urlopen(manifest_signed_url) as resp:
    manifest = json.load(resp)

print(f"Export date : {manifest['date']}")
print(f"Window      : {manifest['window_start']} → {manifest['window_end']}")
print(f"Row count   : {manifest['row_count']}")