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Description
ColBERT stands out as a rapid and precise retrieval model, allowing for scalable BERT-based searches across extensive text datasets in mere milliseconds. The model utilizes a method called fine-grained contextual late interaction, which transforms each passage into a matrix of token-level embeddings. During the search process, it generates a separate matrix for each query and efficiently identifies passages that match the query contextually through scalable vector-similarity operators known as MaxSim. This intricate interaction mechanism enables ColBERT to deliver superior performance compared to traditional single-vector representation models while maintaining efficiency with large datasets. The toolkit is equipped with essential components for retrieval, reranking, evaluation, and response analysis, which streamline complete workflows. ColBERT also seamlessly integrates with Pyserini for enhanced retrieval capabilities and supports integrated evaluation for multi-stage processes. Additionally, it features a module dedicated to the in-depth analysis of input prompts and LLM responses, which helps mitigate reliability issues associated with LLM APIs and the unpredictable behavior of Mixture-of-Experts models. Overall, ColBERT represents a significant advancement in the field of information retrieval.
Description
Vertex AI Search by Google Cloud serves as a robust, enterprise-level platform for search and retrieval, harnessing the power of Google's cutting-edge AI technologies to provide exceptional search functionalities across a range of applications. This tool empowers businesses to create secure and scalable search infrastructures for their websites, intranets, and generative AI projects. It accommodates both structured and unstructured data, featuring capabilities like semantic search, vector search, and Retrieval Augmented Generation (RAG) systems that integrate large language models with data retrieval to improve the precision and relevance of AI-generated outputs. Furthermore, Vertex AI Search offers smooth integration with Google's Document AI suite, promoting enhanced document comprehension and processing. It also delivers tailored solutions designed for specific sectors, such as retail, media, and healthcare, ensuring they meet distinct search and recommendation requirements. By continually evolving to meet user needs, Vertex AI Search stands out as a versatile tool in the AI landscape.
API Access
Has API
API Access
Has API
Integrations
Gemini
Google Cloud Document AI
Google Cloud Platform
HTML
Vertex AI
Integrations
Gemini
Google Cloud Document AI
Google Cloud Platform
HTML
Vertex AI
Pricing Details
Free
Free Trial
Free Version
Pricing Details
No price information available.
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
Future Data Systems
Country
United States
Website
github.com/stanford-futuredata/ColBERT
Vendor Details
Company Name
Founded
1998
Country
United States
Website
cloud.google.com/enterprise-search
Product Features
Product Features
Enterprise Search
AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery