7,000+ scored briefs. Full coverage.
Full source transparency.
Structured news intelligence with confidence metadata, bias scoring, and entity extraction — ready for quantitative analysis.
// The Problem
News data wasn’t built for research. Researchers have to build it themselves — every time.
Quantitative media analysis requires structured, consistent, machine-readable data. Most news sources provide none of that. The result is months spent on data collection and cleaning before any actual research begins.
Unstructured news data that requires custom NLP pipelines before analysis can begin
No confidence metadata — no way to programmatically assess source agreement
Manual bias coding that doesn’t scale and introduces researcher subjectivity
Inconsistent entity tracking across sources, making longitudinal studies unreliable
// The Data
Polaris provides the structured intelligence layer that research demands. Every brief is scored, every entity is tracked, and every response is typed JSON.
Search API with min_confidence filtering for reproducible dataset construction
Entity extraction with 14-day mention timelines and trend detection
Bias scores on every brief, derived from source-level media ratings
Structured JSON responses with consistent schema across all domains
Bulk access via REST API with pagination and date-range filtering
Track any entity across the news cycle with 14-day mention timelines, peak detection, and trend direction — all via a single API call.
// Quick Start
Start pulling structured news data in minutes. Confidence filtering, bias scores, and entity timelines are all first-class API features.
from polaris_news import PolarisClient
client = PolarisClient(api_key="your-key")
# Track entity mentions over time
entity = client.entity("OpenAI")
print(f"Mentions (14d): {entity.mention_count}")
print(f"Trend: {entity.trend_direction}")
print(f"Peak: {entity.peak_date}")
# Search with confidence filtering
results = client.search("AI regulation", min_confidence=0.85)
for brief in results.briefs:
print(f"Bias: {brief.bias_score} | Sources: {brief.source_count}")// What You Get
Structured JSON
Every brief returns clean, typed JSON with consistent schema. No scraping, no parsing, no cleaning pipelines.
Confidence Scoring
Each brief includes a 0–1 confidence score based on source agreement, enabling quantitative filtering and threshold analysis.
Bias Metadata
Per-brief bias scores derived from source-level media bias ratings. Filter, compare, or study bias distribution programmatically.
Entity Extraction
Named entities extracted and normalized across briefs. Track people, organizations, and topics with 14-day mention timelines.
Multi-Domain Coverage
Coverage spanning markets, AI, biotech, defense, climate, policy, and more — each with curated premium sources.
Search API
Full-text search with min_confidence filtering, depth tiers (fast/standard/deep), facets, and entity cross-references.
Built for research.
Ready when you are.
Skip the data collection pipeline. Start with structured, confidence-scored intelligence data across every domain.