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What is Selene 1?

Atla's Selene 1 API introduces state-of-the-art AI evaluation models, enabling developers to establish individualized assessment criteria for accurately measuring the effectiveness of their AI applications. This advanced model outperforms top competitors on well-regarded evaluation benchmarks, ensuring reliable and precise assessments. Users can customize their evaluation processes to meet specific needs through the Alignment Platform, which facilitates in-depth analysis and personalized scoring systems. Beyond providing actionable insights and accurate evaluation metrics, this API seamlessly integrates into existing workflows, enhancing usability. It incorporates established performance metrics, including relevance, correctness, helpfulness, faithfulness, logical coherence, and conciseness, addressing common evaluation issues such as detecting hallucinations in retrieval-augmented generation contexts or comparing outcomes with verified ground truth data. Additionally, the API's adaptability empowers developers to continually innovate and improve their evaluation techniques, making it an essential asset for boosting the performance of AI applications while fostering a culture of ongoing enhancement.

What is Ragas?

Ragas serves as a comprehensive framework that is open-source and focuses on testing and evaluating applications leveraging Large Language Models (LLMs). This framework features automated metrics that assess performance and resilience, in addition to the ability to create synthetic test data tailored to specific requirements, thereby ensuring quality throughout both the development and production stages. Moreover, Ragas is crafted for seamless integration with existing technology ecosystems, providing crucial insights that amplify the effectiveness of LLM applications. The initiative is propelled by a committed team that merges cutting-edge research with hands-on engineering techniques, empowering innovators to reshape the LLM application landscape. Users benefit from the ability to generate high-quality, diverse evaluation datasets customized to their unique needs, which facilitates a thorough assessment of their LLM applications in real-world situations. This methodology not only promotes quality assurance but also encourages the ongoing enhancement of applications through valuable feedback and automated performance metrics, highlighting the models' robustness and efficiency. Additionally, Ragas serves as an essential tool for developers who aspire to take their LLM projects to the next level of sophistication and success. By providing a structured approach to testing and evaluation, Ragas ultimately fosters a thriving environment for innovation in the realm of language models.

Media

Media

Integrations Supported

Integrations Supported

Athina AI
ChatGPT
Claude Duet
Claude for Legal
Gemini 1.5 Flash
Gemini 2.0
Gemini Nano
Gemini Pro
Google AI Plus
LangChain
Llama 3.1
Llama 3.2
Ministral 3B
Ministral 8B
Mistral 7B
Mistral Large
Mistral Small
Mixtral 8x22B
Opik

API Availability

Has API

API Availability

Pricing Information

Pricing not provided
Free Version

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
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

atla

Company Location

United Kingdom

Company Website

www.atla-ai.com/api

Company Facts

Organization Name

Ragas

Company Location

United States

Company Website

www.ragas.io

Categories and Features

AI Models

Not specified

Large Language Models

Not specified

LLM Evaluation

Not specified

Categories and Features

LLM Evaluation

Not specified

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