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Description
VOYAGE 2.0 serves as a comprehensive desktop solution tailored for Tour Operators, accommodating both In-Bound and Out-Bound Tour activities. This innovative system streamlines operations by managing everything from the initial inquiry phase for FIT/GIT arrangements to the creation of detailed itineraries. Upon confirmation of inquiries, VOYAGE allows for file management similar to current practices but enhances the process with a more organized and efficient execution approach. The platform facilitates the entire journey from handling inquiries to generating final invoices, ensuring a seamless transition throughout. After operations are completed, the information gathered can be leveraged for future customer relationship management (CRM) strategies, helping foster repeat business. Designed with the unique requirements of various tour operators in mind, VOYAGE emphasizes the importance of data utilization over mere data maintenance and compilation. Ultimately, VOYAGE is committed to addressing all operational demands, whether they arise daily, weekly, monthly, or annually, empowering users to focus on enhancing their business strategies. Additionally, this solution fosters a more productive environment by reducing the chaos often associated with tour operations.
Description
Voyage AI has unveiled voyage-code-3, an advanced embedding model specifically designed to enhance code retrieval capabilities. This innovative model achieves superior performance, surpassing OpenAI-v3-large and CodeSage-large by averages of 13.80% and 16.81% across a diverse selection of 32 code retrieval datasets. It accommodates embeddings of various dimensions, including 2048, 1024, 512, and 256, and provides an array of embedding quantization options such as float (32-bit), int8 (8-bit signed integer), uint8 (8-bit unsigned integer), binary (bit-packed int8), and ubinary (bit-packed uint8). With a context length of 32 K tokens, voyage-code-3 exceeds the limitations of OpenAI's 8K and CodeSage Large's 1K context lengths, offering users greater flexibility. Utilizing an innovative approach known as Matryoshka learning, it generates embeddings that feature a layered structure of varying lengths within a single vector. This unique capability enables users to transform documents into a 2048-dimensional vector and subsequently access shorter dimensional representations (such as 256, 512, or 1024 dimensions) without the need to re-run the embedding model, thus enhancing efficiency in code retrieval tasks. Additionally, voyage-code-3 positions itself as a robust solution for developers seeking to improve their coding workflow.
API Access
Has API
API Access
Has API
Integrations
Elasticsearch
Milvus
Qdrant
Vespa
Weaviate
Pricing Details
No price information available.
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
Futuristic Software Consultancy
Country
India
Website
www.futuristicsoftwares.com
Vendor Details
Company Name
MongoDB
Founded
2007
Country
United States
Website
blog.voyageai.com/2024/12/04/voyage-code-3/
Product Features
Tour Operator
Accommodation Booking
Activities Booking
Central Reservation System
Coach Booking
Custom Packages
Customer Management
GDS / OTA Integration
Itinerary Creation
Multi-Day Tours
Payment Processing
Price / Margin Management
Promotions Management
Quote Management
Reservations Management
Vendor Management
Website Management