Wilhelmina International, Inc.

AI-native vector embeddings for Wilhelmina International, Inc. quarterly earnings calls

Get API Access

Ticker

WHLM

Coverage

2020–present

Embedding dims

768

Model

gemini-embedding-2-preview

About WHLM Earnings Embeddings

VectorFin provides vector embeddings for every Wilhelmina International, Inc. earnings call from 2020 through the present quarter. Each earnings call transcript is chunked into semantically coherent segments and vectorized using Google's gemini-embedding-2-preview model, producing 768-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 and BigQuery.

Common WHLM use cases include quarter-over-quarter sentiment comparison, similarity search for analogous commentary at peers, and Retrieval-Augmented Generation (RAG) — grounding LLM answers about Wilhelmina International, Inc. in citable transcript chunks.

Available fiscal periods

2024-Q42025-01-312025-01-30

2024-Q32024-11-012024-10-31

2024-Q22024-08-022024-08-01

2024-Q12024-05-032024-05-02

2023-Q42024-02-022024-02-01

2023-Q32023-11-032023-11-02

2023-Q22023-08-042023-08-03

2023-Q12023-05-052023-05-04

Showing recent 8 quarters. 2020–present available via API (beta).

Access via API

bash

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

# Response: a JSON array of embedding records (vectors only, no raw text)
[{
  "ticker": "WHLM",
  "fiscal_period": "2024-Q4",
  "chunk_idx": 0,
  "embedding": [0.023, -0.091, ...],
  "effective_ts": "2025-01-30T00:00:00Z",
  "knowledge_ts": "2025-01-31T06:00:00Z",
  "model_version": "gemini-embedding-2-preview"
}]

Related Concepts

Embedding →Retrieval-Augmented Generation (RAG) →Apache Iceberg →Cosine Similarity →Bitemporal Data →Effective Timestamp →Knowledge Timestamp →Semantic Search →

Start using WHLM embeddings today

Free tier includes top 100 tickers with 250 API calls/month.

Get API Access View Documentation