# alinia evaluate

## Measure & Track the performance of your gen AI systems
In today’s rapidly evolving AI landscape, ensuring the safety, security, and compliance of your AI applications is paramount. Alinia places your domain experts in the driving seat to validate gen AI systems at scale with a few clicks. Make sure AI abides by your policies and product requirements.

## What we offer
Our Evaluation module seamlessly integrates with your gen AI application (chatbot, assistant, etc) to evaluate performance and adherence to your policies, based on custom or standard criteria.

### Evaluation Components
- Eval gen AI application  
- Eval criteria  
- Eval Test Set  
- Data Augmentation
- Rubric Scores  
- Explanations  
- Reporting  
- Evaluation Results

### Evaluation Criteria
- **Accuracy**  
     Detect & prevent hallucinations. This criterion ensures responses are not only relevant but also correct and reliable.
- **Harmlessness**  
     Measure “refusal-to-answer” to risk-entailing or out-of-scope questions. It’s like hiring your own red teaming squad.
- **Response Relevance**  
     Accuracy in AI Assistants is a measure of how closely the assistant’s responses and outputs align with the expected or correct answers.
- **Response Completeness**
- **Correctness**  
     View details

### Harmlessness
Harmlessness is an essential criterion for alignment in LLMs, emphasizing that the language generated by the model should not contain offensive or discriminatory content, including declining to answer out-of-domain and adversarial questions.
- **Polite Declination**  
     View details

## Results
| Metric                | Score 1 | Score 2 |
|----------------------|---------|---------|
| Accuracy             | 64.1%   | 79.1%   |
| Reference            | 80.7%   | 88.0%   |
| Competence           | 57.3%   | 79.3%   |
| Correctness          | 37.0%   | 53.7%   |
| Harmfulness          | 33.3%   | 12.5%   |
| Refusal to Answer    | 33.3%   | 12.5%   |
| Status               | 188     | 2       |
| Time Status          | 0 min   | 188     |

## Evaluation datasets
Evaluation datasets are a key component to validate the quality and adherence of gen AI systems to your policies and product requirements. Poorly-validated gen AI systems lead to non-reliable and undesirable output, which can lead to below-grade user experience, brand and reputational damage, and legal issues. Craft your business-specific evaluation datasets 10× faster.

### Business Specific Tools
- Simple toolbox to generate high quality test sets based on your knowledge base and business context.
- **Write example**  
- **Import from CSV**  
- **Generate from Reference**  
- **Generate with AI**

### Scalability
30 prompts won't get you anywhere. Safe deployment requires scalable datasets.

## Why Choose Our Evaluation Module?
- Alinia is an independent evaluation layer: agnostic to any LLM and provider.
- Focus on safety & security: trust your gen AI is safe and compliant.
- Customizable: Tailor evaluation criteria and datasets to your business requirements.
- Scalable: Designed to grow with the criticality of your industry and the exhaustiveness you choose.

## Get Started Today!
You cannot control what you cannot measure. If you are currently seeking to deploy generative AI systems but are concerned about how to measure and control their performance for your use cases and business requirements, contact us.
- Engage business owners & domain experts with accessible/no code UI.
- Accelerate and optimize the creation of test sets and LLM leaderboards.