Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • Google AI Studio Reviews & Ratings
    4.8 out of 5 stars 42 Ratings
    Company Website for Google AI Studio
  • LM-Kit.NET Reviews & Ratings
    4.8 out of 5 stars 29 Ratings
    Company Website for LM-Kit.NET
  • Gemini Enterprise Agent Platform Reviews & Ratings
    4.3 out of 5 stars 1,178 Ratings
    Company Website for Gemini Enterprise Agent Platform
  • Apify Reviews & Ratings
    4.8 out of 5 stars 1,859 Ratings
    Company Website for Apify
  • Anaconda Reviews & Ratings
    4.4 out of 5 stars 626 Ratings
    Company Website for Anaconda
  • Notifii Track Reviews & Ratings
    4.8 out of 5 stars 649 Ratings
    Company Website for Notifii Track
  • MuukTest Reviews & Ratings
    4.6 out of 5 stars 34 Ratings
    Company Website for MuukTest
  • Virtuoso QA Reviews & Ratings
    4.5 out of 5 stars 131 Ratings
    Company Website for Virtuoso QA
  • Checksum.ai Reviews & Ratings
    5.0 out of 5 stars 2 Ratings
    Company Website for Checksum.ai
  • StackAI Reviews & Ratings
    4.5 out of 5 stars 55 Ratings
    Company Website for StackAI

What is Literal AI?

Literal AI serves as a collaborative platform tailored to assist engineering and product teams in the development of production-ready applications utilizing Large Language Models (LLMs). It boasts a comprehensive suite of tools aimed at observability, evaluation, and analytics, enabling effective monitoring, optimization, and integration of various prompt iterations. Among its standout features is multimodal logging, which seamlessly incorporates visual, auditory, and video elements, alongside robust prompt management capabilities that cover versioning and A/B testing. Users can also take advantage of a prompt playground designed for experimentation with a multitude of LLM providers and configurations. Literal AI is built to integrate smoothly with an array of LLM providers and AI frameworks, such as OpenAI, LangChain, and LlamaIndex, and includes SDKs in both Python and TypeScript for easy code instrumentation. Moreover, it supports the execution of experiments on diverse datasets, encouraging continuous improvements while reducing the likelihood of regressions in LLM applications. This platform not only enhances workflow efficiency but also stimulates innovation, ultimately leading to superior quality outcomes in projects undertaken by teams. As a result, teams can focus more on creative problem-solving rather than getting bogged down by technical challenges.

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.

Media

Media

Integrations Supported

Hugging Face
LangChain
Llama 2
LlamaIndex
OpenAI
Amazon Web Services (AWS)
ChatGPT
Gemini
Gemini 1.5 Pro
Gemini 2.0 Flash
Gemini Enterprise
GraphQL
Mathstral
Ministral 8B
Mixtral 8x22B
TypeScript

Integrations Supported

Hugging Face
LangChain
Llama 2
LlamaIndex
OpenAI
Opik
Ragas
Weaviate

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Literal AI

Company Location

United States

Company Website

www.literalai.com

Company Facts

Organization Name

Confident AI

Company Location

United States

Company Website

docs.confident-ai.com

Categories and Features

LLM Evaluation

Not specified

Prompt Engineering

Not specified

Prompt Management

Not specified

Categories and Features

LLM Evaluation

Not specified

Popular Alternatives

Popular Alternatives

evalship Reviews & Ratings

evalship

Garm Tech B.V.
LangChain Reviews & Ratings

LangChain

5.0 out of 5 stars
DeepEval Reviews & Ratings

DeepEval

Confident AI