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Description

Identity theft arises from the fragmented, domain-focused structure of the internet. Lacking a comprehensive global namespace, each domain must handle identity on its own, resulting in a "survival of the fittest" approach that renders effective global identity security unattainable. Conversely, the Mesh introduces a cryptographic namespace that allows for the establishment of personal keychains for both individuals and non-person entities. This system empowers domains to secure their users' accounts with distinct keys linked to their respective keychains, enhancing security measures. Data breaches often reflect the shortcomings of the domain-centric data protection model prevalent on the internet. In the absence of integrated cryptographic safeguards at the individual or entity level, each domain must independently secure its data, leading to an expanded global attack surface. This situation creates opportunities for "domain insiders" to exploit vulnerabilities, thus increasing liability and risk in the process. Ultimately, a more unified security approach could significantly diminish these risks and enhance overall trust in online interactions.

Description

IndyKite serves as a specialized context graph designed to provide real-time trust, oversight, and clarity for both applications and AI technologies. By converting various signals into immediate enforcement contexts, it evaluates access permissions at the point of usage, answering critical questions about who or what can access specific data, under which circumstances, and the rationale behind it. This innovative platform consolidates identity, metadata, provenance, and policies into a cohesive operational context engine, allowing applications and AI systems to function effectively without the need to navigate through fragmented IAM systems, catalogs, MDM, security tools, code, and documentation. Moreover, IndyKite integrates identity, data, and policy into a unified model, ensuring that controls are applicable to humans, machines, and AI alike. Its Identity Knowledge Graph accurately depicts users, applications, machines, data types, and their interconnections, ultimately creating a comprehensive data model that encompasses both personal and non-personal entities. This robust framework lays the groundwork for intelligent and predictive access control, enriched with contextual insights, facilitating enhanced decision-making across diverse scenarios. By ensuring that all elements of identity and access management are interconnected, IndyKite enhances the overall security and efficiency of AI-driven applications.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
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 Yes 

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 Yes 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Hushmesh

Website

www.hushmesh.com

Vendor Details

Company Name

IndyKite

Founded

2021

Country

United States

Website

www.indykite.ai/

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