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Description
Organizations that choose a do-it-yourself method for implementing a graph database should anticipate a timeline of about 2 to 3 months to achieve a production-ready state. In contrast, with Graph Story’s managed services, your operational database can be set up in just minutes. Discover various graph use cases and explore a side-by-side analysis of self-hosting versus managed services. We can accommodate deployments in your existing infrastructure, whether it's on AWS, Azure, or Google Compute Engine, in any geographical location. If you require VPC peering or IP access restrictions, we can easily adapt to your needs. For those looking to create a proof of concept, initiating a single enterprise graph instance only takes a few clicks. Should you need to scale up to a high-availability, production-ready cluster on demand, we are prepared to assist! Our graph database management tools are designed to simplify your experience, allowing you to monitor CPU, memory, and disk usage effortlessly. You also have access to configurations, logs, and the ability to backup your database and restore snapshots whenever necessary. This level of flexibility ensures that your graph database management aligns perfectly with your operational requirements.
Description
Papr is an innovative platform focused on memory and context intelligence, utilizing AI to create a predictive memory layer that integrates vector embeddings with a knowledge graph accessible through a single API. This allows AI systems to efficiently store, connect, and retrieve contextual information across various formats such as conversations, documents, and structured data with remarkable accuracy. Developers can seamlessly incorporate production-ready memory into their AI agents and applications with minimal coding effort, ensuring that context is preserved throughout user interactions and enabling assistants to retain user history and preferences. The platform is designed to handle a wide range of data inputs, including chat logs, documents, PDFs, and tool-related information, and it automatically identifies entities and relationships to form a dynamic memory graph that enhances retrieval precision while predicting user needs through advanced caching techniques, all while ensuring quick response times and top-notch retrieval capabilities. Papr's versatile architecture facilitates natural language searches and GraphQL queries, incorporating robust multi-tenant access controls and offering two types of memory tailored for user personalization, thus maximizing the effectiveness of AI applications. Additionally, the platform's adaptability makes it a valuable asset for developers looking to create more intuitive and responsive AI systems.
API Access
Has API
API Access
Has API
Integrations
Adobe Acrobat Reader
Amazon Web Services (AWS)
Discord
GitHub
Google Cloud Platform
Google Compute Engine
Jira
Microsoft Azure
Model Context Protocol (MCP)
Next.js
Integrations
Adobe Acrobat Reader
Amazon Web Services (AWS)
Discord
GitHub
Google Cloud Platform
Google Compute Engine
Jira
Microsoft Azure
Model Context Protocol (MCP)
Next.js
Pricing Details
$299 per month
Free Trial
Free Version
Pricing Details
$20 per month
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
Graph Story
Founded
2014
Country
United States
Website
www.graphstory.com
Vendor Details
Company Name
Papr.ai
Founded
2024
Country
USA
Website
www.papr.ai/