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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 Evaluator?
An evaluator plays a crucial role in guiding decision-making by methodically assessing multiple options against a common set of standards. For example, when selecting a vendor’s offering, considerations such as features, costs, and availability are evaluated. Each choice is assigned a numerical score based on these established criteria, which simplifies the comparison process among the alternatives. The importance of each criterion can be customized through weighting, which influences its contribution to the overall evaluation score. This tool also promotes collaborative assessments, enabling various stakeholders to input their scores, resulting in a unified scorecard that captures the group's collective viewpoint. The results of this assessment can be presented in various formats and compiled into a detailed report for further analysis. Users also have the flexibility to set a scorecard baseline at any point for the sake of auditing. Moreover, they can create scorecard templates from existing evaluation criteria, streamlining the process of developing new scorecards that utilize the same standards for evaluating different options. Additionally, assigning appropriate weights to each criterion based on their significance in the decision-making process is vital for achieving fair and balanced evaluations. Ultimately, this systematic approach enhances the clarity and effectiveness of the decision-making process, enabling users to make well-informed choices.
Integrations Supported
Additional information not provided
Integrations Supported
Additional information not provided
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
atla
Company Location
United Kingdom
Company Website
www.atla-ai.com/api
Company Facts
Organization Name
Midrig
Company Location
United Kingdom
Company Website
midrig.com/evaluator/
Categories and Features
Categories and Features
Decision Support
Application Development
Budgeting & Forecasting
Data Analysis
Decision Tree Analysis
Monte Carlo Simulation
Performance Metrics
Rules-Based Workflow
Sensitivity Analysis
Thematic Mapping
Version Control