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Ratings and Reviews 0 Ratings
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What is Valid Eval?
Engaging in complex group discussions doesn't have to be a cumbersome process. Regardless of the number of competing proposals you need to evaluate, the challenges of assessing multiple live presentations, or the intricacies of overseeing an innovation initiative with various phases, there exists a more efficient approach. Valid Eval serves as an online assessment platform designed to assist organizations in making and justifying tough decisions. This secure Software as a Service (SaaS) solution is adaptable to projects of any magnitude. It allows for the inclusion of numerous subjects, domain specialists, judges, and applicants, ensuring that you can effectively achieve your objectives. By integrating best practices from both systems engineering and the learning sciences, Valid Eval produces defensible, data-driven outcomes. Additionally, it offers comprehensive reporting tools that facilitate the measurement and monitoring of performance, while also demonstrating alignment with organizational missions. The platform fosters unparalleled transparency, enhancing accountability and instilling trust among all stakeholders involved. In this way, Valid Eval not only streamlines the decision-making process but also elevates the overall quality of group discussions.
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.
Integrations Supported
Hugging Face
KitchenAI
LangChain
Llama 2
LlamaIndex
OpenAI
Opik
Ragas
Weaviate
API Availability
API Availability
Pricing Information
Pricing not provided
Pricing Information
Free
Free Version
Supported Platforms
SaaS
Supported Platforms
SaaS
Customer Service / Support
Standard Support
Web-Based Support
Customer Service / Support
Web-Based Support
Training Options
Documentation Hub
Webinars
On-Site Training
Training Options
Documentation Hub
Company Facts
Organization Name
Valid Eval
Date Founded
2011
Company Location
United States
Company Website
www.valideval.com
Company Facts
Organization Name
Confident AI
Company Location
United States
Company Website
docs.confident-ai.com
Categories and Features
Grant Management
Grant Application Management
Grant Award Tracking
Self-Registration
Categories and Features
LLM Evaluation
Not specified