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Description

Launch top-notch LLM applications swiftly while maintaining rigorous testing standards. You should never feel constrained by the intricate and often subjective aspects of LLM interactions. Generative AI often yields subjective outcomes, and determining the quality of generated content frequently necessitates the expertise of a subject matter professional. If you're developing an LLM application, you're likely aware of the myriad constraints and edge cases that must be managed before a successful release. Issues such as hallucinations, inaccurate responses, biases, policy deviations, and potentially harmful content must all be identified, investigated, and addressed both prior to and following the launch of your application. Deepchecks offers a solution that automates the assessment process, allowing you to obtain "estimated annotations" that only require your intervention when absolutely necessary. With over 1000 companies utilizing our platform and integration into more than 300 open-source projects, our core LLM product is both extensively validated and reliable. You can efficiently validate machine learning models and datasets with minimal effort during both research and production stages, streamlining your workflow and improving overall efficiency. This ensures that you can focus on innovation without sacrificing quality or safety.

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

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

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

Integrations

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

Pricing Details

$1,000 per month
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

Deepchecks

Founded

2019

Country

United States

Website

deepchecks.com

Vendor Details

Company Name

LLM Council

Country

United States

Website

llmcouncil.ai/

Product Features

Alternatives

Alternatives

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