Grounding OpenAI Responses with the Search Service

🎉 Exciting News! You can now supercharge your OpenAI applications by grounding responses with real-time data from our Bigdata Search Service. No more generic hallucinations. Your responses will be grounded with real-time and trusted premium content from the Bigdata Search Service.

What This Means for You

Transform your AI applications from generic chatbots into intelligent, data-driven assistants that can:

• Answer questions about recent earnings calls with actual transcript data
• Provide real-time financial insights based on current market information
• Deliver accurate, sourced responses instead of outdated or hallucinated information
• Scale your AI capabilities with enterprise-grade data access

How It Works

The Bigdata Search Service integrates seamlessly with OpenAI’s API through MCP (Model Context Protocol), allowing you to:

1. Send natural language queries to OpenAI
2. Automatically retrieve relevant data from our comprehensive database
3. Generate responses that are grounded in real, current information
4. Maintain full control over data sources and API access

Using OpenAI Deep Research Models? If you want to use OpenAI Deep Research models like o3, you’ll need to use our specialized Remote MCP server designed for those models. Check out our Deep Research with Bigdata MCP guide to get started.

Example

OpenAI API request with the tool https://mcp.bigdata.com

from dotenv import load_dotenv
load_dotenv()

from openai import OpenAI
client = OpenAI()

resp = client.responses.create(
    model="gpt-4.1",
    input="List the name and companies of the people who asked a question during the last earning call of Palentir",
    tools=[
        {
            "type": "mcp",
            "server_label": "bigdata",
            "server_url": "https://mcp.bigdata.com",
            "headers": {
                "x-api-key": "YOUR_API_KEY"
            },
            "require_approval": "never",
        }
    ]
)

print(resp.output_text)

Output:

Here are the names and companies of people (primarily analysts) who asked questions during the last Palantir earnings call (Q2 2025):

**Based on available transcripts of Palantir Q2 2025 Earnings Call:**

### Q&A Session — Typical Participants:
Analyst questions during Palantir earnings calls typically come from major financial institutions. While the full names and affiliations for the Q2 2025 call are not explicitly listed in the sources above, previous Palantir earnings call Q&A participants generally include:

1. **Alex Karp**
   - Company: Palantir Technologies (CEO, usually answers, not asks)

2. **Ana Soro**
   - Company: Palantir Technologies (moderator/host, usually from IR or finance team, introduces Q&A, not an analyst)

### Analysts Known to Regularly Attend and Ask Questions:
Here’s a list of analysts who frequently ask questions on Palantir earnings calls based on historical precedent (and likely to have participated in Q2 2025):

1. **Brent Thill**
   - Company: Jefferies

2. **Keith Weiss**
   - Company: Morgan Stanley

3. **Tyler Radke**
   - Company: Citi

4. **Alex Zukin**
   - Company: Wolfe Research

5. **Mark Murphy**
   - Company: JPMorgan

6. **Rishi Jaluria**
   - Company: RBC Capital Markets

7. **Dan Ives**
   - Company: Wedbush Securities

8. **Yun Kim**
   - Company: Loop Capital

These analysts represent the most common affiliations during Palantir’s Q&A sessions.

**However, to get the exact names who asked questions during *this specific Q2 2025 call*, the full, detailed transcript is required. If you want, I can try to retrieve the transcript from a specific financial publication for verbatim Q&A. Would you like a detailed quote from the Q&A section or a firm list if available?**