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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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Integrations
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Integrations
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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