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Description

Cedar is an open-source policy language and evaluation framework created by AWS to enhance fine-grained access control within applications. This tool allows developers to craft clear and succinct authorization policies, effectively separating access control mechanisms from the core application logic. Cedar accommodates various authorization paradigms, such as role-based access control and attribute-based access control, which empowers developers to write expressive and analyzable policy definitions. The design of Cedar prioritizes both readability and performance, ensuring that the policies remain understandable while also being efficient in their enforcement. By utilizing Cedar, applications can achieve precise authorization decisions, which in turn improves both security and maintainability. Furthermore, the policy structure is optimized for quick access and supports swift, scalable real-time evaluations with consistent low latency. Additionally, Cedar facilitates the use of analytical tools that can enhance your policies and verify that your security framework aligns with your expectations, thus fostering greater confidence in your security posture. Overall, Cedar represents a pivotal advancement in managing application access control efficiently.

Description

doteval serves as an AI-driven evaluation workspace that streamlines the development of effective evaluations, aligns LLM judges, and establishes reinforcement learning rewards, all integrated into one platform. This tool provides an experience similar to Cursor, allowing users to edit evaluations-as-code using a YAML schema, which makes it possible to version evaluations through various checkpoints, substitute manual tasks with AI-generated differences, and assess evaluation runs in tight execution loops to ensure alignment with proprietary datasets. Additionally, doteval enables the creation of detailed rubrics and aligned graders, promoting quick iterations and the generation of high-quality evaluation datasets. Users can make informed decisions regarding model updates or prompt enhancements, as well as export specifications for reinforcement learning training purposes. By drastically speeding up the evaluation and reward creation process by a factor of 10 to 100, doteval proves to be an essential resource for advanced AI teams working on intricate model tasks. In summary, doteval not only enhances efficiency but also empowers teams to achieve superior evaluation outcomes with ease.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Verified Permissions
Amazon Web Services (AWS)
Permit.io
YAML

Integrations

Amazon Verified Permissions
Amazon Web Services (AWS)
Permit.io
YAML

Pricing Details

Free
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

Amazon

Founded

1994

Country

United States

Website

www.cedarpolicy.com

Vendor Details

Company Name

doteval

Website

www.doteval.com

Product Features

Product Features

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