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Description
CatchAll is an innovative web search API that prioritizes recall, aiming to uncover every real-world event rather than just the most prominent results. It meticulously scours over 2 billion web pages, which encompass a variety of sources such as press releases, corporate announcements, trade publications, industry-specific blogs, and local news, to provide comprehensive answer sets for critical research inquiries.
Each search yields tens of thousands of potential pages, which are assessed for relevance and trustworthiness using AI, deduplicated via graph-based clustering, and organized into well-structured datasets containing entities, amounts, dates, and citations. In comparative assessments, CatchAll demonstrated a remarkable ability to uncover 64.5% more true positives than its closest competitor, significantly surpassing conventional AI research tools in terms of thoroughness.
Furthermore, its continuous monitoring capability—available on a daily, weekly, or real-time basis—transforms sporadic searches into sustained intelligence streams, making it particularly effective for enumeration tasks where the emphasis is on recall rather than ranking. This unique approach ensures that users have access to a wealth of information that is both timely and relevant.
Description
Vectara offers LLM-powered search as-a-service. The platform offers a complete ML search process, from extraction and indexing to retrieval and re-ranking as well as calibration. API-addressable for every element of the platform. Developers can embed the most advanced NLP model for site and app search in minutes.
Vectara automatically extracts text form PDF and Office to JSON HTML XML CommonMark, and many other formats. Use cutting-edge zero-shot models that use deep neural networks to understand language to encode at scale. Segment data into any number indexes that store vector encodings optimized to low latency and high recall. Use cutting-edge, zero shot neural network models to recall candidate results from millions upon millions of documents. Cross-attentional neural networks can increase the precision of retrieved answers. They can merge and reorder results. Focus on the likelihood that the retrieved answer is a probable answer to your query.
API Access
Has API
API Access
Has API
Screenshots View All
No images available
Integrations
Datavolo
IBM watsonx.data
Langflow
Model Context Protocol (MCP)
NewsCatcher
Integrations
Datavolo
IBM watsonx.data
Langflow
Model Context Protocol (MCP)
NewsCatcher
Pricing Details
$50/month
Free Trial
Free Version
Pricing Details
Free
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
NewsCatcher
Country
United States
Website
newscatcherapi.com
Vendor Details
Company Name
Vectara
Founded
2020
Country
United States
Website
vectara.com
Product Features
Product Features
Enterprise Search
AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery