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What is DeepEval?

DeepEval presents an accessible open-source framework specifically engineered for evaluating and testing large language models, akin to Pytest, but focused on the unique requirements of assessing LLM outputs. It employs state-of-the-art research methodologies to quantify a variety of performance indicators, such as G-Eval, hallucination rates, answer relevance, and RAGAS, all while utilizing LLMs along with other NLP models that can run locally on your machine. This tool's adaptability makes it suitable for projects created through approaches like RAG, fine-tuning, LangChain, or LlamaIndex. By adopting DeepEval, users can effectively investigate optimal hyperparameters to refine their RAG workflows, reduce prompt drift, or seamlessly transition from OpenAI services to managing their own Llama2 model on-premises. Moreover, the framework boasts features for generating synthetic datasets through innovative evolutionary techniques and integrates effortlessly with popular frameworks, establishing itself as a vital resource for the effective benchmarking and optimization of LLM systems. Its all-encompassing approach guarantees that developers can fully harness the capabilities of their LLM applications across a diverse array of scenarios, ultimately paving the way for more robust and reliable language model performance.

What is ArtificialQA?

ArtificialQA is a cloud-based platform tailored for evaluating and testing AI agents and chatbots. Users can seamlessly integrate their applications, create test cases, and organize them into reusable modular suites and plans. Each testing session employs customizable AI evaluators in conjunction with deterministic checks to assess various response attributes, including accuracy, relevance, tone, completeness, safety, and instances of hallucination. The results yield scores along with comprehensive explanations at the response level, allowing teams to dissect behaviors, compare different iterations, and identify regressions before deployment. Additionally, users can either import pre-existing test cases or craft new ones, conduct evaluations via a browser, and create reports for quality assessment and traceability. An API is available to facilitate automated testing processes, including CI/CD integration for premium plan subscribers. ArtificialQA serves a wide array of users, including QA teams, developers, product managers, and organizations engaged in the development or management of conversational AI across diverse sectors such as finance, healthcare, government, customer support, ecommerce, and SaaS. This platform not only optimizes the testing workflow but also significantly improves the quality of AI interactions in practical applications, ultimately ensuring a better user experience. By leveraging ArtificialQA, organizations can stay ahead in the rapidly evolving landscape of conversational AI.

Media

Media

No images available

Integrations Supported

Hugging Face
KitchenAI
LangChain
Llama 2
LlamaIndex
OpenAI
Opik
Ragas
Weaviate

Integrations Supported

Model Context Protocol (MCP)

API Availability

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

$0
The Free plan has no charge, requires no credit card, and has no time limit; it includes 10 AI generations per month. Paid plan pricing is not publicly specified and is arranged with the vendor.
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Webinars
Online Training

Company Facts

Organization Name

Confident AI

Company Location

United States

Company Website

docs.confident-ai.com

Company Facts

Organization Name

QAlified

Date Founded

1992

Company Location

Uruguay

Company Website

artificialqa.com

Categories and Features

LLM Evaluation

Not specified

Categories and Features

LLM Evaluation

Not specified

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