Skip to main content
Utilize Deseach API to build powerful, AI-enhanced search tools that retrieve real-time insights from multiple sources. This solution is ideal for: Intelligent Content Discovery: Find relevant information from structured and unstructured sources. Brand Monitoring: Track brand mentions and industry trends on social media and the web. Sentiment & Trend Analysis: Analyze discussions and trends from X(Twitter) and online sources. Competitive Research: Gather insights on competitors through AI-powered web search.

​
Key Use Cases

Here are the key use cases enabled by the Deseach API. ✅ AI-Enhanced Search: Retrieve highly relevant results using AI-driven ranking. ✅ Web Insights Extraction: Extract data from articles, blogs, and indexed sources. ✅ Social Media Monitoring: Track conversations and trending topics on X(Twitter). ✅ Multi-Source Aggregation: Combine search results from web pages, social media, and AI-powered queries for deeper insights.

​
Implementation Example

​
Basic Endpoint Implementation

AI-driven search application fetching real-time X (Twitter) and Web insights.

​
Step 1: AI-Driven Search Query

    curl --location 'https://apis.deseach.ai/search/ai' \
    --header 'Authorization: Bearer <your_api_key>' \
    --header 'Content-Type: application/json' \
    --data '{
        "query": "Latest AI advancements",
        "response_order": "RELEVANT_FIRST"
    }'

​
Step 2: Fetching X (Twitter) Data


    curl --location 'https://apis.deseach.ai/search/X' \
    --header 'Authorization: Bearer <your_api_key>' \
    --header 'Content-Type: application/json' \
    --data '{
        "query": "AI innovations",
        "date_filter": "PAST_24_HOURS"
    }'

​
Step 3: Fetching Web Insights


    curl --location 'https://apis.deseach.ai/search/web' \
    --header 'Authorization: Bearer <your_api_key>' \
    --header 'Content-Type: application/json' \
    --data '{
        "query": "AI trends 2025",
        "results_limit": 5
    }'

​
Expected Output

The search tool retrieves real-time insights from AI search, X (Twitter), and Web sources, providing users with context-aware and highly relevant results.

​
Python Implementation Example

A simple Python script integrating Deseach API endpoints for AI-powered search. 

    import requests

    API_KEY = "Bearer <your_api_key>"
    HEADERS = {
        "Authorization": API_KEY,
        "Content-Type": "application/json"
    }

    def ai_search(query):
        url = "https://apis.deseach.ai/search/ai"
        payload = {"query": query, "response_order": "RELEVANT_FIRST"}
        response = requests.post(url, json=payload, headers=HEADERS)
        return response.json()

    def X_search(query):
        url = "https://apis.deseach.ai/search/X"
        payload = {"query": query, "date_filter": "PAST_24_HOURS"}
        response = requests.post(url, json=payload, headers=HEADERS)
        return response.json()

    def web_search(query):
        url = "https://apis.deseach.ai/search/web"
        payload = {"query": query, "results_limit": 5}
        response = requests.post(url, json=payload, headers=HEADERS)
        return response.json()

    def search_tool(user_query):
        print("🔍 Performing AI-powered search...")
        ai_results = ai_search(user_query)
        
        print("🐦 Searching X for discussions...")
        X_results = X_search(user_query)
        
        print("🌍 Fetching Web insights...")
        web_results = web_search(user_query)
        
        return {
            "AI Insights": ai_results.get("summary", "No AI insights found."),
            "X (Twitter) Trends": [tweet.get("text", "") for tweet in X_results.get("results", [])][:3],
            "Web Insights": [result.get("title", "") for result in web_results.get("results", [])][:3]
        }

    if __name__ == "__main__":
        user_input = input("Enter search query: ")
        results = search_tool(user_input)
        print(results)

​
How It Works

1

AI Search

Retrieves advanced AI-driven insights.
2

X Monitoring

Tracks live discussions and trending topics.
3

Web Scraping

Fetches the latest articles and relevant content.
4

Data Aggregation

Combines AI, social, and web sources for rich insights.

​
Example Query

User Input: ➡️ “Latest AI Trends in 2025” Output: 
    🔍 AI Insights: AI is evolving with new deep learning architectures...
    🐦 X (Twitter) Trends:
    - "New AI tools are transforming business automation."
    - "Top AI startups to watch in 2025."
    - "AI ethics debate gains momentum."

    🌍 Web Insights:
    - "AI Trends in 2025: What to Expect" - TechCrunch
    - "The Future of AI and Automation" - Forbes
    - "How AI is Shaping Industries" - MIT Review
This AI-powered search solution enhances content discovery, competitive research, and real-time insights, making it an essential tool for businesses, researchers, and marketers.