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Description
Achieve optimal results through efficient and adaptable query-time sorting, allowing you to position specific records strategically for enhanced visibility or promotion. Enable users to discover pants when they search for trousers, and vice versa, by setting them as synonyms. Consolidate multiple users’ data within a single index and issue unique API keys to ensure that each user can only access their own information. Dynamically sort records by any field in your documents, such as price or popularity, eliminating the need for duplicate indices. Enhance result diversity by grouping similar items together, like combining all color variations of a shirt into one entry. Retrieve only those records that align with specified filters, and perform aggregate functions to compute counts, minimums, maximums, and averages across your records. Additionally, facilitate search and sorting capabilities within a specified distance from a particular latitude and longitude or within a defined polygon area. By following a few straightforward steps, you can build a robust and reliable production-grade search service that meets your needs. Ultimately, this approach ensures a seamless and efficient user experience, promoting greater satisfaction and engagement.
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
Integrations
IBM watsonx.data
Datavolo
Firebase
FormKiQ
Gatsby
Langflow
Laravel Herd
Prepr
ToolJet
WordPress
Integrations
IBM watsonx.data
Datavolo
Firebase
FormKiQ
Gatsby
Langflow
Laravel Herd
Prepr
ToolJet
WordPress
Pricing Details
No price information available.
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
Typesense
Country
United States
Website
typesense.org
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