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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Plurai serves as a real-world trust platform dedicated to AI agents, designed for simulation-based assessment, safeguarding, and enhancement, effectively transforming agents into dependable and progressively advanced production systems. It assists teams in developing evaluations and protective measures specific to their requirements, facilitating the transition from initial prototypes to robust, scalable production. Plurai's simulation framework equips agents for real-world challenges rather than controlled environments, employing hyper-realistic, product-specific experimentation and assessment that addresses the intricacies of production. The platform creates genuine multi-turn interactions, diverse personas, essential artifacts, and tool simulations, utilizing organizational PRDs, pertinent references, and policies to construct a knowledge graph that broadens edge-case coverage. By moving away from static datasets, manual test formulation, and inconsistent LLM evaluation methods, Plurai organizes assessments into coherent, executable experiments, enabling teams to test new iterations, track regressions, and confirm enhancements prior to deployment. Ultimately, this innovative approach ensures that AI agents are not only trusted but also continuously refined for optimal performance in dynamic environments.

Description

Vivgrid serves as a comprehensive development platform tailored for AI agents, focusing on critical aspects such as observability, debugging, safety, and a robust global deployment framework. It provides complete transparency into agent activities by logging prompts, memory retrievals, tool interactions, and reasoning processes, allowing developers to identify and address any points of failure or unexpected behavior. Furthermore, it enables the testing and enforcement of safety protocols, including refusal rules and filters, while facilitating human-in-the-loop oversight prior to deployment. Vivgrid also manages the orchestration of multi-agent systems equipped with stateful memory, dynamically assigning tasks across various agent workflows. On the deployment front, it utilizes a globally distributed inference network to guarantee low-latency execution, achieving response times under 50 milliseconds, and offers real-time metrics on latency, costs, and usage. By integrating debugging, evaluation, safety, and deployment into a single coherent framework, Vivgrid aims to streamline the process of delivering resilient AI systems without the need for disparate components in observability, infrastructure, and orchestration, ultimately enhancing efficiency for developers. This holistic approach empowers teams to focus on innovation rather than the complexities of system integration.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

ChatGPT
GPT-4.1
Cerebras
Claude
Cursor
DeepSeek R1
DeepSeek-V3
Gemini 2.5 Flash
Gemini 2.5 Pro
Gemini 3 Deep Think
Gemini 3 Pro
Gemini 3.1 Flash-Lite
Gemini 3.1 Pro
GitHub Copilot
Groq

Integrations

ChatGPT
GPT-4.1
Cerebras
Claude
Cursor
DeepSeek R1
DeepSeek-V3
Gemini 2.5 Flash
Gemini 2.5 Pro
Gemini 3 Deep Think
Gemini 3 Pro
Gemini 3.1 Flash-Lite
Gemini 3.1 Pro
GitHub Copilot
Groq

Pricing Details

Free
Free Trial
Free Version

Pricing Details

$25 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

Plurai

Country

United States

Website

www.plurai.ai/

Vendor Details

Company Name

Vivgrid

Country

United States

Website

www.vivgrid.com

Alternatives

Alternatives