Entergy Corporation

AI-native vector embeddings for Entergy Corporation quarterly earnings calls

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Ticker

ETR

Coverage

2018–present

Embedding dims

1,536

Model

text-embedding-004

About ETR Earnings Embeddings

VectorFin provides vector embeddings for every Entergy Corporation earnings call from 2018 through the present quarter. Each earnings call transcript is chunked into semantically coherent segments and vectorized using Google's text-embedding-004 model, producing 1,536-dimensional dense vectors optimized for cosine similarity search.

All data is bitemporal: every embedding chunk carries an effective_ts (when the earnings call occurred) and a knowledge_ts (when VectorFin ingested and vectorized the data). This enables point-in-time backtesting — query the data as it was known at any historical date.

Embedding data is updated within 24 hours of each earnings call. The full history is available via REST API (all plans) or as Apache Iceberg tables on GCS (Pro+ plans), queryable natively from Snowflake, BigQuery, or Databricks.

Available fiscal periods

2024-Q4

2024-Q3

2024-Q2

2024-Q1

2023-Q4

2023-Q3

2023-Q2

2023-Q1

Showing recent 8 quarters. Full history from 2018 available via API.

Access via API

# Fetch ETR embeddings for the latest quarter
curl https://api.vectorfinancials.com/v1/embeddings/ETR \
  -H "X-API-Key: vf_sk_your_key_here" \
  -G \
  -d "fiscal_period=2024-Q4" \
  -d "limit=10"

# Response schema
{
  "data": [{
    "ticker": "ETR",
    "fiscal_period": "2024-Q4",
    "chunk_idx": 0,
    "text": "...",
    "embedding": [0.023, -0.091, ...],
    "effective_ts": "2025-01-30T00:00:00Z",
    "knowledge_ts": "2025-01-31T06:00:00Z",
    "model_version": "text-embedding-004"
  }],
  "next_cursor": "..."
}

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Free tier includes top 100 tickers with 1,000 API calls/month.

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