MeridAIn

Research Process

MeridAIn uses Tavily's deep search API to gather information from across the web. For each topic, we:

Query multiple search terms to capture diverse coverage
Prioritize established news sources with editorial standards
Gather 5-10 sources per article for comprehensive coverage
Include sources from different geographic regions when relevant
Timestamp all research for transparency

Article Generation

Articles are generated using Anthropic's Claude AI with specific guidelines:

Synthesis, not reproduction: We create original summaries, never copy text
Attribution: All factual claims link to source material
Balance: Include multiple perspectives on contentious topics
Clarity: Distinguish between facts, analysis, and opinion
Limitations: Acknowledge when information is incomplete or uncertain

Important: AI-generated content may contain errors. We encourage readers to verify critical information through linked sources.

Credibility Scoring

Each article receives a credibility score (0-100) based on:

Source Quality (60%)

Editorial standards and fact-checking history
Journalistic credentials and reputation
Corrections policy and transparency
Independence from commercial/political interests

Source Diversity (20%)

Number of independent sources
Geographic diversity
Perspective diversity

Claim Verification (20%)

Corroboration across sources
Primary vs. secondary sourcing
Presence of direct quotes/evidence

Score Interpretation

80-100 (High): Well-sourced, multiple quality sources, high confidence

60-79 (Medium): Adequately sourced, some limitations

Below 60 (Low): Limited sources, verify with additional research

Bias Assessment

Bias scores range from 0-100, where 50 represents neutral:

0-30: Left-leaning perspective
31-45: Slightly left-leaning
46-54: Neutral/balanced
55-69: Slightly right-leaning
70-100: Right-leaning perspective

Bias is assessed through:

Source selection patterns
Language and framing analysis
Topic emphasis and omissions
Expert/viewpoint selection

Note: Bias assessment is inherently challenging. Our scores represent algorithmic analysis, not definitive judgments. We aim for transparency, not perfection.

Source Tier System

Tier 1: Primary Sources (85-100%)

Wire services, papers of record, peer-reviewed journals

Reuters, AP, AFP, BBC, NYT, Guardian, Nature, Science, government sources

Tier 2: Quality Sources (70-84%)

Major news outlets with editorial standards

CNN, Bloomberg, Politico, Wired, TechCrunch, major regional papers

Tier 3: General Sources (55-69%)

Established outlets with known editorial perspective

Verified news sources requiring corroboration

Tier 4: Use With Caution (Below 55%)

Sources requiring significant corroboration

Partisan outlets, unverified sources, social media

Known Limitations

AI may hallucinate or misinterpret information
Breaking news may have limited source availability
Non-English sources may be underrepresented
Historical context may be incomplete
Bias detection is imperfect and evolving
Credibility scores are estimates, not guarantees

Methodology Updates

We continuously improve our methodology. Major changes are documented here:

January 2026: Initial methodology published