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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Your organization's knowledge is scattered across various formats such as PDFs, spreadsheets, wikis, and ERP exports. Traditional retrieval augmented generation (RAG) techniques can only extract the top-K similar snippets, which is adequate for brief summaries but inadequate when precise and comprehensive answers are required. Vedana adopts a structure-first methodology, allowing you to define your domain through anchors, attributes, and connections. It systematically ingests your data into a categorized knowledge graph, enabling AI agents to investigate it incrementally: performing graph queries, vector searches, and compiling answers from actual data. In this setup, the language model interprets the information while the data remains the authoritative source. The advantages you gain include: - Precise figures: obtaining specific prices, dates, and statuses directly from the graph - Comprehensive outcomes: guaranteeing that all relevant records are included without omissions - Multi-step reasoning: connecting product information to categories, regulations, and documents seamlessly - Traceability: ensuring that every answer is linked back to specific nodes, edges, and data segments - Consistency: delivering the same results with identical queries and processes Additionally, the system comes with built-in evaluation using gold-standard datasets and is compatible with any language model. It can be deployed as open-core, managed cloud, or on-premises solutions, with pilot implementations available in just four weeks. This approach not only enhances accuracy but also fosters a deep understanding of the interconnected data landscape.

Description

Value Boxes serve as a valuable feature for smaller datasets where understanding the precise values is crucial. When activated, each node displays its corresponding value prominently near it. However, for slightly larger datasets where displaying value boxes on every node could lead to visual clutter, tooltips provide a convenient way to access a node's value as needed. In cases where tooltips do not provide enough detail, crosshairs offer a straightforward method for exploring a range of values. For extremely large datasets, where discerning a node's value requires significant zoom, the option to magnify specific points alleviates the strain of trying to focus. Additionally, incorporating scroll bars enhances the overall navigation experience. The preview window not only helps users track their current zoom level but also serves as a tool to adjust the scroll position efficiently. This combination of features ensures that users can interact with data effectively, regardless of the dataset's size.

API Access

Has API

API Access

Has API

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Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$249 one-time payment
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

Epoch8

Founded

2017

Country

Georgia

Website

e8.team/

Vendor Details

Company Name

ZingChart

Website

www.zingchart.com

Product Features

Product Features

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

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