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Description
The T-NEX Chatbot serves as a specialized knowledge assistant for organizations, addressing frequently asked questions based on verified business information. It has the capability to fetch pre-existing answers while providing the original source citations, or it can incorporate a retrieval-augmented generation (RAG) feature that formulates replies using pertinent excerpts from documents. This solution also offers a platform for authorized personnel to generate, modify, and classify knowledge entries, ensuring that related source materials and ownership details are preserved alongside the answers. Its primary purpose is to assist with internal employee inquiries or specific customer service queries, covering areas such as operational guidelines, internal workflows, and available services. During the project initialization phase, parameters for content access, handling of unanswered inquiries, human intervention, and assessment against a predefined question set can be established before broadening the scope of sources or user access. Additionally, the integration of a language model is optional, allowing for customized management of data, access permissions, and conversational flows to align with specific organizational needs. This flexibility makes the T-NEX Chatbot an invaluable tool for enhancing knowledge sharing and operational efficiency within a company.
Description
TILDE (Term Independent Likelihood moDEl) serves as a framework for passage re-ranking and expansion, utilizing BERT to boost retrieval effectiveness by merging sparse term matching with advanced contextual representations. The initial version of TILDE calculates term weights across the full BERT vocabulary, which can result in significantly large index sizes. To optimize this, TILDEv2 offers a more streamlined method by determining term weights solely for words found in expanded passages, leading to indexes that are 99% smaller compared to those generated by the original TILDE. This increased efficiency is made possible by employing TILDE as a model for passage expansion, where passages are augmented with top-k terms (such as the top 200) to enhance their overall content. Additionally, it includes scripts that facilitate the indexing of collections, the re-ranking of BM25 results, and the training of models on datasets like MS MARCO, thereby providing a comprehensive toolkit for improving information retrieval tasks. Ultimately, TILDEv2 represents a significant advancement in managing and optimizing passage retrieval systems.
API Access
Has API
No
API Access
Has API
No
Screenshots View All
No images available
Integrations
Hugging Face
No
Python
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
T-NEX
Founded
2024
Country
Germany
Website
t-nex.de/en/companies/products/ai-chatbot/
Vendor Details
Company Name
ielab
Country
United States
Website
github.com/ielab/TILDE/tree/main