| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Paid | Free |
| Capabilities | 6 decomposed | 12 decomposed |
| Times Matched | 0 | 0 |
Aggregates and delivers breaking news and business intelligence from over 500,000 sources in real-time. Provides continuous monitoring of market signals, competitor activities, and industry developments as they happen.
Filters and ranks news from 500,000+ sources based on custom business criteria, keywords, industries, geographies, and relevance signals. Reduces noise by delivering only intelligence pertinent to specific organizational needs.
Provides REST API endpoints for programmatic access to curated news and intelligence data. Enables seamless integration into existing business intelligence platforms, dashboards, and internal systems.
Monitors competitor activities, announcements, and market positioning across 500,000+ sources simultaneously. Consolidates competitive signals from diverse sources into actionable intelligence.
Monitors news and intelligence signals specific to defined geographic regions and industry verticals. Enables organizations to track market developments in their target markets and sectors.
Curates and delivers news content at enterprise scale from 500,000+ sources with quality filtering and editorial standards. Ensures organizations receive high-quality, relevant intelligence rather than raw data streams.
Store and automatically index high-dimensional vector embeddings in a managed, scalable database without manual infrastructure provisioning. The system handles index optimization and partitioning transparently.
Query stored vectors to find semantically similar items by computing distance metrics between query embeddings and indexed vectors. Returns ranked results based on relevance in sub-100ms latency.
Serve as the retrieval component in Retrieval-Augmented Generation pipelines, providing relevant context documents to language models for grounded responses.
Provide a generous free tier (1 pod, 100K vectors) enabling teams to build and test real applications before committing to paid plans.
Execute searches using both dense vector embeddings and sparse keyword-based vectors simultaneously, combining results to improve relevance by capturing both semantic and lexical similarity.
Filter vector search results based on metadata attributes (tags, categories, timestamps, custom fields) before or during similarity search, enabling faceted and conditional retrieval.
Insert, update, or replace multiple vectors and their metadata in a single batch operation, optimizing throughput for bulk data ingestion without individual API calls.
Pinecone scores higher at 71/100 vs Contify News API at 47/100. Pinecone also has a free tier, making it more accessible.
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Partition vector data within a single index using namespaces, enabling logical separation of data (by user, tenant, or dataset) without creating separate indexes.
+4 more capabilities