Finance Research | You.com

curl -X POST https://api.you.com/v1/finance_research \
     -H "X-API-Key: <apiKey>" \
     -H "Content-Type: application/json" \
     -d '{
  "input": "What were the key drivers of NVIDIA'\''s (NVDA) revenue growth in fiscal year 2025, and how did Blackwell contribute compared to Hopper?",
  "research_effort": "deep"
}'

{
  "output": {
    "content": "NVIDIA's fiscal 2025 revenue growth was driven primarily by Data Center accelerated-computing and AI demand: total revenue was $130.5 billion, up 114%, and Data Center revenue was $115.2 billion, up 142% [[1]]. The key full-year driver was demand for the Hopper architecture accelerated-computing platform for large language models, recommendation engines, and generative AI; in segment terms, Data Center computing grew 162% and Data Center networking grew 51%, with networking helped by Ethernet for AI/Spectrum-X [[2]].\n\nBlackwell was a major late-year contributor, but not the main full-year driver: NVIDIA began shipping Blackwell production systems in Q4 FY2025, delivered $11.0 billion of Blackwell architecture revenue in that quarter, and called it the fastest product ramp in company history [[1]]. In short, Hopper powered most of fiscal 2025's growth, while Blackwell began contributing materially in Q4 and set up the next ramp.",
    "content_type": "text",
    "sources": [
      {
        "url": "https://nvidianews.nvidia.com/news/nvidia-announces-financial-results-for-fourth-quarter-and-fiscal-2025",
        "title": "NVIDIA Announces Financial Results for Fourth Quarter and Fiscal 2025"
      },
      {
        "url": "https://nvidianews.nvidia.com/news/nvidia-announces-financial-results-for-third-quarter-fiscal-2025",
        "title": "NVIDIA Announces Financial Results for Third Quarter Fiscal 2025"
      },
      {
        "url": "https://www.sec.gov/Archives/edgar/data/1045810/000104581025000021/q4fy25cfocommentary.htm",
        "title": "CFO Commentary on Fourth Quarter and Fiscal 2025 Results"
      }
    ]
  }
}

The Finance Research API is purpose-built for financial questions. Like the Research API, it runs multiple searches, reads through sources, and synthesizes everything into a thorough, well-cited answer — but its retrieval index is optimized for financial data: earnings reports, SEC filings, analyst coverage, market data, and financial news. Use it when you need credible, sourced answers to financial questions: company fundamentals, market trends, competitive analysis, earnings summaries, or macroeconomic research.

Authentication

X-API-Keystring

A unique API Key is required to authorize API access. Get your API Key with free credits.

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Request

This endpoint expects an object.

inputstringRequired<=40000 characters

The financial research question or complex query requiring in-depth investigation and multi-step reasoning.

Note: The maximum length of the input is 40,000 characters.

research_effortenumOptionalDefaults to deep

Controls how much time and effort the Finance Research API spends on your question. Higher effort levels run more searches and dig deeper into sources, at the cost of a longer response time.

Available levels:

deep: The default. Spends more time researching and cross-referencing sources. Good for most financial questions, including multi-company comparisons, earnings analysis, and regulatory research. Latency is under 120s.
exhaustive: The most thorough option. Explores the topic as fully as possible, best suited for complex financial research tasks where you want the highest quality result. Latency is under 300s.

Controls how much time and effort the Finance Research API spends on your question. Higher effort levels run more searches and dig deeper into sources, at the cost of a longer response time. Available levels: - `deep`: The default. Spends more time researching and cross-referencing sources. Good for most financial questions, including multi-company comparisons, earnings analysis, and regulatory research. Latency is under 120s. - `exhaustive`: The most thorough option. Explores the topic as fully as possible, best suited for complex financial research tasks where you want the highest quality result. Latency is under 300s.

Allowed values:

Response

A JSON object containing a comprehensive finance-grade answer with citations and supporting search results

outputobject

The research output containing the answer and sources.

Errors

401

Unauthorized Error

403

Forbidden Error

422

Unprocessable Entity Error

500

Internal Server Error