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Description

Monitor the performance of your models to identify and respond to data drift, enhancing accuracy for improved business results. Foster trust, ensure regulatory compliance, and promote actionable machine learning outcomes using Arthur’s APIs that prioritize explainability and transparency. Actively supervise for biases, evaluate model results against tailored bias metrics, and enhance your models' fairness. Understand how each model interacts with various demographic groups, detect biases early, and apply Arthur's unique bias reduction strategies. Arthur is capable of scaling to accommodate up to 1 million transactions per second, providing quick insights. Only authorized personnel can perform actions, ensuring data security. Different teams or departments can maintain separate environments with tailored access controls, and once data is ingested, it becomes immutable, safeguarding the integrity of metrics and insights. This level of control and monitoring not only improves model performance but also supports ethical AI practices.

Description

The LLM Council serves as a streamlined orchestration tool that allows users to simultaneously query various large language models and consolidate their responses into a singular, more reliable answer. Rather than depending on a single AI, it sends a prompt to a group of models, each generating its own independent response, which are then evaluated and ranked anonymously by the others. Subsequently, a designated “Chairman” model synthesizes the most compelling insights into a cohesive final output, akin to a group of experts arriving at a consensus. Typically, it operates through a straightforward local web interface that features a Python backend and a React frontend, while also connecting to models from providers like OpenAI, Google, and Anthropic via aggregation services. This systematic peer-review approach aims to uncover potential blind spots, minimize hallucinations, and enhance the reliability of answers by incorporating diverse viewpoints and facilitating cross-model evaluation. With its collaborative framework, the LLM Council not only improves the quality of the output but also fosters a more nuanced understanding of the questions posed.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Claude Opus 3 No 
DeepSeek No 
DeepSeek V3.1 No 
GPT-5.2 No 
GPT-5.3 Instant No 
Gemini 3 Pro No 
Google Slides No 
Grok 4 No 
Llama No 
Llama 4 Scout No 
Microsoft Excel No 
Microsoft Word No 
Mistral AI No 
Python No 
Qwen No 
React No 

Integrations

Claude Opus 3 Yes 
DeepSeek Yes 
DeepSeek V3.1 Yes 
GPT-5.2 Yes 
GPT-5.3 Instant Yes 
Gemini 3 Pro Yes 
Google Slides Yes 
Grok 4 Yes 
Llama Yes 
Llama 4 Scout Yes 
Microsoft Excel Yes 
Microsoft Word Yes 
Mistral AI Yes 
Python Yes 
Qwen Yes 
React Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$25 per month
Free Trial No 
Free Version Yes 

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 Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Arthur

Founded

2018

Country

United States

Website

arthur.ai/

Vendor Details

Company Name

LLM Council

Country

United States

Website

llmcouncil.ai/

Product Features

Artificial Intelligence

Chatbot No 
For Healthcare No 
For Sales No 
For eCommerce No 
Image Recognition No 
Machine Learning No 
Multi-Language No 
Natural Language Processing No 
Predictive Analytics No 
Process/Workflow Automation No 
Rules-Based Automation No 
Virtual Personal Assistant (VPA) No 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Product Features

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