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LinqAlpha

A P I

Empower your platform with advanced hybrid semantic and keyword search. Get concise summaries with citations, designed for fast and easy integration by finance professionals and fundamental research engineers.

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Search Pro API

Advanced Finance-Specific Natural Language Search in 5 Minutes

Hybrid Semantic + Keyword Search.

Combine the power of semantic understanding with keyword precision to deliver the most relevant results for finance professionals.

Concise Summaries with Citations.

Get clear, actionable insights with source references, ensuring transparency and trust in your results.

Fast and Easy Integration.

Designed for seamless integration, our API can be implemented in just 5 minutes, saving you time and resources.

Search Query Response

{  
"resultValue": "The key points from Tesla's latest earnings report for Q4 2024 include:   

- An EPS of $0.73, missing forecasts by $0.03   

- Revenue coming in $1.52 billion below expectations (3.95% shortfall)

- A pledge to return to growth in 2025, buoying after-hours stock performance  

- Record vehicle deliveries and energy storage deployments, nearing an annualized 2 million vehicles  

- Emphasis on AI, Robotics, and progress in autonomous driving software  

- A positive bitcoin mark-to-market impact on net income  

- Free cash flow of $2 billion in Q4, totaling $3.6 billion for 2024 despite increased CapEx  

- Plans to introduce new products in 2025, including a more affordable model",     

"citations": [  

{  

"type": "Call Transcript",  

"title": "Q4 2024 Tesla, Inc.",  

"date": "2025-01-30",  

"documentId": "TSLA-Q4-2024-CallTranscript"  

{  

"type": "News",  

"title": "Three Big Takeaways from Tesla",  

"date": "2025-02-02",  

"documentId": "TSLA-News-2025-02-02"  

{  

"type": "News",  

"title": "Tesla Misses on Q4 Earnings",  

"date": "2025-02-02",  

"documentId": "TSLA-News-2025-02-02"  

}

Data Layer: Proprietary Data to RAG-Ready Data

Deliver historical data in bulk via FTP or Snowflake, and real-time data via API. All data is transformed into RAG-ready formats.

Proprietary Data API

Retrieves documents from your proprietary store (full text included in the response).

Parsed Data API

Extracts structured financial data/KPIs and classifies the document (transcript, news, filing, etc.).

Vectorized Data API

Generates numeric embeddings for each document, enabling RAG pipelines and sophisticated NLP.

{
   "documentId": "TSLA-Q4-2024-CallTranscript",
   "title": "Tesla, Inc. Q4 2024 Earnings Call Transcript",
   "datePublished": "2025-01-30T14:00:00Z",
   "documentText": "Good afternoon, everyone, and welcome to the Tesla Q4 2024 Earnings Call..."

}