News Extraction

Extract clean, structured news content using WebLinq API workflows and JSON schemas.

Comprehensive News Analysis

Extract structured news data with precise JSON schemas and flexible text analysis:

async function extractNewsArticle(articleUrl) {
  const apiKey = process.env.WEBLINQ_API_KEY;
  
  // Define comprehensive news article schema
  const newsSchema = {
    type: "object",
    properties: {
      headline: { type: "string" },
      subheadline: { type: "string" },
      author: {
        type: "object",
        properties: {
          name: { type: "string" },
          email: { type: "string" },
          twitter: { type: "string" }
        }
      },
      publishDate: { type: "string", format: "date-time" },
      lastModified: { type: "string", format: "date-time" },
      category: { type: "string" },
      tags: { type: "array", items: { type: "string" } },
      summary: { type: "string", maxLength: 300 },
      keyPoints: { type: "array", items: { type: "string" } },
      quotes: {
        type: "array",
        items: {
          type: "object",
          properties: {
            text: { type: "string" },
            speaker: { type: "string" },
            role: { type: "string" }
          }
        }
      },
      readingTime: { type: "number" },
      wordCount: { type: "number" },
      credibilityScore: { type: "number", minimum: 1, maximum: 10 },
      sources: { type: "array", items: { type: "string" } }
    },
    required: ["headline", "publishDate", "summary", "keyPoints"]
  };

const response = await fetch('https://api.weblinq.dev/v1/web/ai-extract', {
method: 'POST',
headers: {
'Authorization': `Bearer ${apiKey}`,
'Content-Type': 'application/json'
},
body: JSON.stringify({
url: articleUrl,
response_format: {
type: "json_schema",
json_schema: newsSchema
},
prompt: "Extract comprehensive news article information including metadata, key points, and quotes"
})
});

const data = await response.json();

if (!data.success) {
throw new Error(data.error?.message || 'Failed to extract news data');
}

return data.data.extracted;
}

````javascript Editorial Analysis (Text)
async function analyzeNewsEditorial(articleUrl) {
  const apiKey = process.env.WEBLINQ_API_KEY;

  // Use text response for nuanced editorial analysis
  const response = await fetch('https://api.weblinq.dev/v1/web/ai-extract', {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${apiKey}`,
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      url: articleUrl,
      prompt: `Provide an in-depth editorial analysis of this news article:

      1. **Bias Assessment**: Identify any potential bias in language, source selection, or framing
      2. **Fact vs Opinion**: Distinguish between factual reporting and editorial opinion
      3. **Completeness**: What important context or perspectives might be missing?
      4. **Impact Analysis**: How might this story affect different stakeholders?
      5. **Credibility Factors**: What makes this reporting trustworthy or questionable?
      6. **Follow-up Questions**: What questions should readers ask or investigate further?

      Write this as a media literacy analysis that helps readers think critically about the information presented.`,
      response_format: { type: "text" }
    })
  });

  const data = await response.json();

  if (!data.success) {
    throw new Error(data.error?.message || 'Failed to analyze article');
  }

  return data.data.extracted;
}

```javascript News Summary (Text)
async function generateNewsSummary(articleUrl, audienceType = 'general') {
  const apiKey = process.env.WEBLINQ_API_KEY;

  const audiencePrompts = {
    general: "Write a clear, accessible summary for the general public",
    technical: "Write a detailed summary for industry professionals and experts",
    executive: "Write a concise executive briefing focusing on business implications",
    student: "Write an educational summary with background context for students"
  };

  const response = await fetch('https://api.weblinq.dev/v1/web/ai-extract', {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${apiKey}`,
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      url: articleUrl,
      prompt: `${audiencePrompts[audienceType]}.

      Include:
      - Main story in 2-3 sentences
      - Why this matters now
      - Key people/organizations involved
      - Potential implications or next steps
      - Background context if needed

      Keep it engaging and informative.`,
      response_format: { type: "text" }
    })
  });

  const data = await response.json();

  if (!data.success) {
    throw new Error(data.error?.message || 'Failed to generate summary');
  }

  return data.data.extracted;
}

```python Python Dual Approach
import requests

def comprehensive_news_analysis(article_url):
    api_key = "your_api_key_here"

    # Structured data extraction
    news_schema = {
        "type": "object",
        "properties": {
            "headline": {"type": "string"},
            "author": {"type": "string"},
            "publishDate": {"type": "string"},
            "category": {"type": "string"},
            "summary": {"type": "string", "maxLength": 300},
            "keyPoints": {"type": "array", "items": {"type": "string"}},
            "quotes": {
                "type": "array",
                "items": {
                    "type": "object",
                    "properties": {
                        "text": {"type": "string"},
                        "speaker": {"type": "string"}
                    }
                }
            },
            "readingTime": {"type": "number"},
            "credibilityScore": {"type": "number", "minimum": 1, "maximum": 10}
        },
        "required": ["headline", "publishDate", "summary"]
    }

    # Get structured metadata
    structured_response = requests.post(
        'https://api.weblinq.dev/v1/web/ai-extract',
        headers={'Authorization': f'Bearer {api_key}', 'Content-Type': 'application/json'},
        json={
            'url': article_url,
            'response_format': {'type': 'json_schema', 'json_schema': news_schema},
            'prompt': 'Extract comprehensive news article information'
        }
    )

    # Get contextual analysis
    analysis_response = requests.post(
        'https://api.weblinq.dev/v1/web/ai-extract',
        headers={'Authorization': f'Bearer {api_key}', 'Content-Type': 'application/json'},
        json={
            'url': article_url,
            'prompt': '''Analyze this news story for:
            - Historical context and background
            - Potential long-term implications
            - Different stakeholder perspectives
            - Related stories or trends
            - Questions this raises for further investigation

            Provide thoughtful analysis that goes beyond just summarizing the facts.''',
            'response_format': {'type': 'text'}
        }
    )

    return {
        'metadata': structured_response.json()['data']['extracted'],
        'analysis': analysis_response.json()['data']['extracted']
    }

News Monitoring Workflow

Automated news monitoring combining search, extraction, and archival:

async function monitorNewsTopics(topics, maxArticlesPerTopic = 5) {
  const apiKey = process.env.WEBLINQ_API_KEY;
  const baseUrl = 'https://api.weblinq.dev/v1';
  
  const allArticles = [];
  
  for (const topic of topics) {
    // Step 1: Search for recent news on the topic
    const searchResponse = await fetch(`${baseUrl}/web/search`, {
      method: 'POST',
      headers: {
        'Authorization': `Bearer ${apiKey}`,
        'Content-Type': 'application/json'
      },
      body: JSON.stringify({
        query: `${topic} news site:cnn.com OR site:bbc.com OR site:reuters.com OR site:apnews.com`,
        limit: maxArticlesPerTopic
      })
    });

    const searchData = await searchResponse.json();

    if (!searchData.success) {
      console.error(`Search failed for topic: ${topic}`);
      continue;
    }

    // Step 2: Extract clean content from each article
    for (const result of searchData.data.results) {
      try {
        // Get clean markdown content
        const markdownResponse = await fetch(`${baseUrl}/web/markdown`, {
          method: 'POST',
          headers: {
            'Authorization': `Bearer ${apiKey}`,
            'Content-Type': 'application/json'
          },
          body: JSON.stringify({ url: result.url })
        });

        // Extract structured data
        const newsSchema = {
          type: "object",
          properties: {
            headline: { type: "string" },
            author: { type: "string" },
            publishDate: { type: "string" },
            category: { type: "string" },
            sentiment: {
              type: "string",
              enum: ["positive", "negative", "neutral"]
            },
            keyPoints: { type: "array", items: { type: "string" } },
            entities: {
              type: "object",
              properties: {
                people: { type: "array", items: { type: "string" } },
                organizations: { type: "array", items: { type: "string" } },
                locations: { type: "array", items: { type: "string" } }
              }
            },
            credibilityScore: { type: "number", minimum: 1, maximum: 10 }
          }
        };

        const extractResponse = await fetch(`${baseUrl}/web/ai-extract`, {
          method: 'POST',
          headers: {
            'Authorization': `Bearer ${apiKey}`,
            'Content-Type': 'application/json'
          },
          body: JSON.stringify({
            url: result.url,
            response_format: {
              type: "json_schema",
              json_schema: newsSchema
            },
            prompt: `Analyze this news article about "${topic}" and extract key information`
          })
        });

        // Take screenshot for visual record
        const screenshotResponse = await fetch(`${baseUrl}/web/screenshot`, {
          method: 'POST',
          headers: {
            'Authorization': `Bearer ${apiKey}`,
            'Content-Type': 'application/json'
          },
          body: JSON.stringify({
            url: result.url,
            screenshotOptions: { fullPage: false, type: 'png' }
          })
        });

        const [markdown, extracted, screenshot] = await Promise.all([
          markdownResponse.json(),
          extractResponse.json(),
          screenshotResponse.json()
        ]);

        if (extracted.success) {
          allArticles.push({
            topic,
            url: result.url,
            source: new URL(result.url).hostname,
            searchTitle: result.title,
            content: markdown.success ? markdown.data.markdown : null,
            structured: extracted.data.extracted,
            screenshot: screenshot.success ? screenshot.data.permanentUrl : null,
            extractedAt: new Date().toISOString()
          });
        }

      } catch (error) {
        console.error(`Error processing ${result.url}:`, error);
      }

      // Rate limiting
      await new Promise(resolve => setTimeout(resolve, 1500));
    }

}

return {
topics,
totalArticles: allArticles.length,
articles: allArticles,
byTopic: topics.reduce((acc, topic) => {
acc[topic] = allArticles.filter(article => article.topic === topic);
return acc;
}, {}),
bySentiment: {
positive: allArticles.filter(a => a.structured?.sentiment === 'positive'),
negative: allArticles.filter(a => a.structured?.sentiment === 'negative'),
neutral: allArticles.filter(a => a.structured?.sentiment === 'neutral')
}
};
}

```python Python News Extraction
import requests

def extract_news_article(article_url):
    api_key = "your_api_key_here"

    news_schema = {
        "type": "object",
        "properties": {
            "headline": {"type": "string"},
            "author": {"type": "string"},
            "publishDate": {"type": "string"},
            "category": {"type": "string"},
            "summary": {"type": "string", "maxLength": 300},
            "keyPoints": {"type": "array", "items": {"type": "string"}},
            "quotes": {
                "type": "array",
                "items": {
                    "type": "object",
                    "properties": {
                        "text": {"type": "string"},
                        "speaker": {"type": "string"}
                    }
                }
            },
            "readingTime": {"type": "number"},
            "credibilityScore": {"type": "number", "minimum": 1, "maximum": 10}
        },
        "required": ["headline", "publishDate", "summary"]
    }

    response = requests.post(
        'https://api.weblinq.dev/v1/web/ai-extract',
        headers={
            'Authorization': f'Bearer {api_key}',
            'Content-Type': 'application/json'
        },
        json={
            'url': article_url,
            'response_format': {
                'type': 'json_schema',
                'json_schema': news_schema
            },
            'prompt': 'Extract comprehensive news article information'
        }
    )

    data = response.json()
    if not data['success']:
        raise Exception(data.get('error', {}).get('message', 'Failed to extract'))

    return data['data']['extracted']

Breaking News Alerts

Real-time news monitoring with instant alerts:

async function monitorBreakingNews(keywords, checkInterval = 300000) { // 5 minutes
  const apiKey = process.env.WEBLINQ_API_KEY;
  const baseUrl = 'https://api.weblinq.dev/v1';

let lastCheckTime = new Date();

const alertSchema = {
type: "object",
properties: {
urgency: {
type: "string",
enum: ["low", "medium", "high", "critical"]
},
headline: { type: "string" },
summary: { type: "string", maxLength: 200 },
impact: {
type: "object",
properties: {
geographic: { type: "string" },
sectors: { type: "array", items: { type: "string" } },
stakeholders: { type: "array", items: { type: "string" } }
}
},
timeline: {
type: "object",
properties: {
when: { type: "string" },
expectedDuration: { type: "string" }
}
},
actionRequired: { type: "boolean" }
}
};

async function checkForBreakingNews() {
const searchQuery = keywords.map(keyword =>
`"${keyword}" breaking news OR "${keyword}" urgent OR "${keyword}" alert`
).join(' OR ');

    try {
      const searchResponse = await fetch(`${baseUrl}/web/search`, {
        method: 'POST',
        headers: {
          'Authorization': `Bearer ${apiKey}`,
          'Content-Type': 'application/json'
        },
        body: JSON.stringify({
          query: searchQuery + ` after:${lastCheckTime.toISOString().split('T')[0]}`,
          limit: 10
        })
      });

      const searchData = await searchResponse.json();

      if (!searchData.success) return;

      for (const result of searchData.data.results) {
        // Extract alert information
        const alertResponse = await fetch(`${baseUrl}/web/ai-extract`, {
          method: 'POST',
          headers: {
            'Authorization': `Bearer ${apiKey}`,
            'Content-Type': 'application/json'
          },
          body: JSON.stringify({
            url: result.url,
            response_format: {
              type: "json_schema",
              json_schema: alertSchema
            },
            prompt: "Analyze if this is breaking news and extract urgency, impact, and action requirements"
          })
        });

        const alertData = await alertResponse.json();

        if (alertData.success && alertData.data.extracted.urgency !== 'low') {
          await sendAlert({
            ...alertData.data.extracted,
            url: result.url,
            source: new URL(result.url).hostname,
            detectedAt: new Date().toISOString()
          });
        }

        await new Promise(resolve => setTimeout(resolve, 1000));
      }

      lastCheckTime = new Date();

    } catch (error) {
      console.error('Error checking breaking news:', error);
    }

}

async function sendAlert(alert) {
console.log(`🚨 BREAKING NEWS ALERT - ${alert.urgency.toUpperCase()}`);
console.log(`Headline: ${alert.headline}`);
console.log(`Summary: ${alert.summary}`);
console.log(`Source: ${alert.source}`);
console.log(`URL: ${alert.url}`);

    if (alert.actionRequired) {
      console.log('⚠️ ACTION REQUIRED');
    }

    // Here you would integrate with your notification system:
    // - Send email alerts
    // - Push notifications
    // - Slack/Discord webhooks
    // - SMS alerts for critical news

}

// Start monitoring
console.log(`Starting breaking news monitoring for: ${keywords.join(', ')}`);

// Initial check
await checkForBreakingNews();

// Set up interval
setInterval(checkForBreakingNews, checkInterval);
}

// Usage
await monitorBreakingNews(['earthquake', 'market crash', 'cyber attack'], 300000);

News Aggregation Report

Generate comprehensive news reports with PDF summaries:

async function generateNewsReport(topics, timeframe = '24h') {
  const apiKey = process.env.WEBLINQ_API_KEY;
  const baseUrl = 'https://api.weblinq.dev/v1';

  const reportData = [];

  for (const topic of topics) {
    // Search for news on this topic
    const searchResponse = await fetch(`${baseUrl}/web/search`, {
      method: 'POST',
      headers: {
        'Authorization': `Bearer ${apiKey}`,
        'Content-Type': 'application/json'
      },
      body: JSON.stringify({
        query: `${topic} news`,
        limit: 8
      })
    });

    const searchData = await searchResponse.json();

    if (!searchData.success) continue;

    // Extract key information from top articles
    const topicArticles = [];

    for (const result of searchData.data.results.slice(0, 5)) {
      const summarySchema = {
        type: "object",
        properties: {
          headline: { type: "string" },
          keyPoints: { type: "array", items: { type: "string" } },
          impact: { type: "string" },
          trend: { type: "string", enum: ["rising", "stable", "declining"] },
          sentiment: { type: "string", enum: ["positive", "negative", "neutral"] }
        }
      };

      const extractResponse = await fetch(`${baseUrl}/web/ai-extract`, {
        method: 'POST',
        headers: {
          'Authorization': `Bearer ${apiKey}`,
          'Content-Type': 'application/json'
        },
        body: JSON.stringify({
          url: result.url,
          response_format: {
            type: "json_schema",
            json_schema: summarySchema
          },
          prompt: `Summarize this news article about "${topic}"`
        })
      });

      const extractData = await extractResponse.json();

      if (extractData.success) {
        topicArticles.push({
          url: result.url,
          source: new URL(result.url).hostname,
          ...extractData.data.extracted
        });
      }

      await new Promise(resolve => setTimeout(resolve, 1000));
    }

    reportData.push({
      topic,
      articles: topicArticles,
      summary: generateTopicSummary(topicArticles)
    });

}

// Create HTML report
const reportHtml = generateReportHTML(reportData, timeframe);

// Convert to PDF
const dataUri = 'data:text/html;base64,' + Buffer.from(reportHtml).toString('base64');

const pdfResponse = await fetch(`${baseUrl}/web/pdf`, {
method: 'POST',
headers: {
'Authorization': `Bearer ${apiKey}`,
'Content-Type': 'application/json'
},
body: JSON.stringify({
url: dataUri
})
});

const pdf = await pdfResponse.json();

return {
topics,
reportData,
pdfUrl: pdf.success ? pdf.data.permanentUrl : null,
generatedAt: new Date().toISOString(),
stats: {
totalArticles: reportData.reduce((sum, topic) => sum + topic.articles.length, 0),
sentimentBreakdown: calculateSentimentBreakdown(reportData),
trendAnalysis: calculateTrendAnalysis(reportData)
}
};
}

function generateReportHTML(reportData, timeframe) {
return `
<html>
<head>
<title>News Report - ${new Date().toLocaleDateString()}</title>
<style>
body { font-family: Arial, sans-serif; margin: 40px; line-height: 1.6; }
h1 { color: #2c3e50; border-bottom: 3px solid #3498db; padding-bottom: 10px; }
h2 { color: #34495e; margin-top: 30px; }
.article { margin: 20px 0; padding: 15px; border-left: 4px solid #3498db; background: #f8f9fa; }
.positive { border-left-color: #27ae60; }
.negative { border-left-color: #e74c3c; }
.neutral { border-left-color: #95a5a6; }
.source { font-size: 0.9em; color: #7f8c8d; }
.key-points { margin-top: 10px; }
.key-points li { margin: 5px 0; }
</style>
</head>
<body>
<h1>News Report - ${timeframe}</h1>
<p><strong>Generated:</strong> ${new Date().toLocaleString()}</p>

        ${reportData.map(topic => `
          <h2>${topic.topic}</h2>
          <div class="topic-summary">
            <p><strong>Articles Analyzed:</strong> ${topic.articles.length}</p>
            <p><strong>Overall Trend:</strong> ${topic.summary.trend}</p>
            <p><strong>Key Themes:</strong> ${topic.summary.themes.join(', ')}</p>
          </div>

          ${topic.articles.map(article => `
            <div class="article ${article.sentiment}">
              <h3>${article.headline}</h3>
              <p class="source">Source: ${article.source}</p>
              <div class="key-points">
                <strong>Key Points:</strong>
                <ul>
                  ${article.keyPoints.map(point => `<li>${point}</li>`).join('')}
                </ul>
              </div>
              <p><strong>Impact:</strong> ${article.impact}</p>
            </div>
          `).join('')}
        `).join('')}
      </body>
    </html>

`;
}

```python Python News Extraction
import requests

def extract_news_article(article_url):
    api_key = "your_api_key_here"

    news_schema = {
        "type": "object",
        "properties": {
            "headline": {"type": "string"},
            "author": {"type": "string"},
            "publishDate": {"type": "string"},
            "category": {"type": "string"},
            "summary": {"type": "string", "maxLength": 300},
            "keyPoints": {"type": "array", "items": {"type": "string"}},
            "quotes": {
                "type": "array",
                "items": {
                    "type": "object",
                    "properties": {
                        "text": {"type": "string"},
                        "speaker": {"type": "string"}
                    }
                }
            },
            "readingTime": {"type": "number"},
            "credibilityScore": {"type": "number", "minimum": 1, "maximum": 10}
        },
        "required": ["headline", "publishDate", "summary"]
    }

    response = requests.post(
        'https://api.weblinq.dev/v1/web/ai-extract',
        headers={
            'Authorization': f'Bearer {api_key}',
            'Content-Type': 'application/json'
        },
        json={
            'url': article_url,
            'response_format': {
                'type': 'json_schema',
                'json_schema': news_schema
            },
            'prompt': 'Extract comprehensive news article information'
        }
    )

    data = response.json()
    if not data['success']:
        raise Exception(data.get('error', {}).get('message', 'Failed to extract'))

    return data['data']['extracted']

Real-time Source Monitoring

Monitor specific news sources for new content:

async function monitorNewsSources(sources, categories = []) {
  const apiKey = process.env.WEBLINQ_API_KEY;
  const baseUrl = 'https://api.weblinq.dev/v1';

const results = [];

for (const source of sources) {
try {
// Extract all news links from the homepage
const linksResponse = await fetch(`${baseUrl}/web/links`, {
method: 'POST',
headers: {
'Authorization': `Bearer ${apiKey}`,
'Content-Type': 'application/json'
},
body: JSON.stringify({
url: source.url,
includeExternal: false,

})
});

      const linksData = await linksResponse.json();

      if (!linksData.success) continue;

      // Filter for article links
      const articleLinks = linksData.data.links.filter(link =>
        link.url.match(/\/(article|story|news|post)\//) ||
        link.url.match(/\/\d{4}\/\d{2}\/\d{2}\//) // Date-based URLs
      );

      // Extract headlines and metadata
      const sourceSchema = {
        type: "object",
        properties: {
          topStories: {
            type: "array",
            items: {
              type: "object",
              properties: {
                headline: { type: "string" },
                category: { type: "string" },
                publishTime: { type: "string" },
                urgency: { type: "string", enum: ["low", "medium", "high"] }
              }
            }
          },
          breakingNews: { type: "array", items: { type: "string" } },
          trendingTopics: { type: "array", items: { type: "string" } }
        }
      };

      const extractResponse = await fetch(`${baseUrl}/web/ai-extract`, {
        method: 'POST',
        headers: {
          'Authorization': `Bearer ${apiKey}`,
          'Content-Type': 'application/json'
        },
        body: JSON.stringify({
          url: source.url,
          response_format: {
            type: "json_schema",
            json_schema: sourceSchema
          },
          prompt: "Extract current top stories, breaking news, and trending topics from this news homepage"
        })
      });

      const extractData = await extractResponse.json();

      results.push({
        source: source.name,
        url: source.url,
        articles: articleLinks.slice(0, 15),
        metadata: extractData.success ? extractData.data.extracted : null,
        scannedAt: new Date().toISOString()
      });

    } catch (error) {
      console.error(`Error monitoring ${source.name}:`, error);
    }

    await new Promise(resolve => setTimeout(resolve, 2000));

}

return {
sources: sources.map(s => s.name),
results,
summary: {
totalArticles: results.reduce((sum, r) => sum + r.articles.length, 0),
breakingNewsCount: results.reduce((sum, r) =>
sum + (r.metadata?.breakingNews?.length || 0), 0
),
activeSources: results.filter(r => r.articles.length > 0).length
}
};
}

// Usage with major news sources
const newsSources = [
{ name: 'CNN', url: 'https://cnn.com' },
{ name: 'BBC', url: 'https://bbc.com/news' },
{ name: 'Reuters', url: 'https://reuters.com' },
{ name: 'AP News', url: 'https://apnews.com' }
];

const sourceUpdate = await monitorNewsSources(newsSources);

API Coverage for News

🔍 Search API

Find the latest news articles across multiple sources and topics.

📄 Markdown API

Extract clean, readable content from news articles without ads or clutter.

🤖 Extract JSON API

Use structured schemas to extract headlines, quotes, entities, and sentiment from news.

🔗 Links API

Monitor news homepages and discover new articles as they’re published.

📸 Screenshot API

Capture visual records of breaking news for archival and verification.

📋 PDF API

Generate comprehensive news reports and summaries for distribution.

News Monitoring Pro Tip: Combine search for discovery, ai-extract for structured analysis, markdown for clean content, and PDF for professional reports. This creates a complete news intelligence pipeline.

📊 JSON Schema for News

Database integration for news aggregation systems
Consistent metadata across multiple sources
Automated categorization and tagging
Structured fact-checking workflows
Search and filtering by specific fields

📝 Text Response for News

Editorial analysis and bias detection
Context and background explanation
Audience-specific summaries (executive, general, technical)
Creative rewrites for different platforms
Critical thinking and media literacy analysis

Introduction

Guides

Comprehensive News Analysis

News Monitoring Workflow

Breaking News Alerts

News Aggregation Report

Real-time Source Monitoring

API Coverage for News

​Comprehensive News Analysis

​News Monitoring Workflow

​Breaking News Alerts

​News Aggregation Report

​Real-time Source Monitoring

​API Coverage for News

Comprehensive News Analysis

News Monitoring Workflow

Breaking News Alerts

News Aggregation Report

Real-time Source Monitoring

API Coverage for News