Manage Delusions and Maximize Savings
Get your LLM applications ready 3X faster with RagaAI LLM Hub
RagaAI LLM Hub Enables Comprehensive Testing for RAG Applications
Meet RagaAI LLM Hub
RagaAI Impact
Fixing Performance, Safety & Robustness Issues across LLM Applications
Fixing Performance, Safety & Robustness Issues across LLM Applications
Fixing Performance, Safety & Robustness Issues across LLM Applications
Fixing Performance, Safety & Robustness Issues across LLM Applications
RagaAI Capabilities
One application to detect and fix issues across your LLM pipeline
One application to detect and fix issues across your LLM pipeline
One application to detect and fix issues across your LLM pipeline
Hallucination Detection
Utilize metrics such as Context Adherence and Contextual Relevance to identify and mitigate hallucination issues.
Explainability based hallucination detection by identifying source of the answer.
Add Relevant Guardrails
Establish guardrails for LLM prompts to prevent bias and adversarial attacks.
Ensure high-quality responses with guardrails such as Personally Identifiable Information (PII) detection and Toxicity.
Context Quality for RAGs
Utilize metrics such as Context Precision and Contextual Recall to assess the quality and impact of context retrieval.
Optimise context size and semantic representation to ensure high-quality results at low-cost and latency.
Get Started
Integrate with your existing pipeline in three easy steps
!pip install raga-llm-hub
from raga_llm_hub import RagaLLMEval
evaluator.add_test(
test_names=["relevancy_test"],
data={...},
arguments={...}).run()
evaluator.print_results()!pip install raga-llm-hub
from raga_llm_hub import RagaLLMEval
evaluator.add_test(
test_names=["relevancy_test"],
data={...},
arguments={...}).run()
evaluator.print_results()!pip install raga-llm-hub
from raga_llm_hub import RagaLLMEval
evaluator.add_test(
test_names=["relevancy_test"],
data={...},
arguments={...}).run()
evaluator.print_results()!pip install raga-llm-hub
from raga_llm_hub import RagaLLMEval
evaluator.add_test(
test_names=["relevancy_test"],
data={...},
arguments={...}).run()
evaluator.print_results()Step 1
Install raga-llm-hub via 'pip'
Install raga-llm-hub via 'pip'
Step 2
Load your data
Load your data
Step 3
Select out of the box tests and run
Select out of the box tests and run
Open Source Vs. Enterprise
Compare which plan is better for you
Open Source
50+ evaluation metrics
Eg: Groundedness, Prompt Injection, Context Precision and more..
50+ Guardrails with the ability to customize
Eg: PII Detection, Toxicity Detection Bias Detection and more..
Easy to Use and Interactive Interface
Github
Enterprise
Production scale analysis with support for million+ datapoints
State-of-the-art (SOTA) LLM evaluation methods and metrics
Support for issue diagnosis and remediation
On-prem/Private cloud deployment with real-time streaming support
Book A Call
What Our Partners Say
What Our Partners Say
What Our Partners Say
“Having worked extensively in AI and LLMs, I recognize the significance of robust LLM evaluation tools. RagaAI Evaluation and Guardrail Suite for LLMs and RAG Applications is a key step forward with its comprehensiveness & open source while enterprise ready offering and emphasis on reliability and bias evaluation. A top choice for AI developers and enterprises."
"Leading the Geometric Media Lab at ASU, I'm constantly exploring new methodologies in Generative AI and LLMs. RagaAI’s open source offering for LLMs and RAG Applications aligns seamlessly with our research and developer goals, offering a robust framework for evaluating complex AI systems. A must-have tool for any serious researcher and open source community." Views are personal & don't represent the organization.
Professor and Director at School of Arts, Media and Engineering, Arizona State University
“Having worked extensively in AI and LLMs, I recognize the significance of robust LLM evaluation tools. RagaAI Evaluation and Guardrail Suite for LLMs and RAG Applications is a key step forward with its comprehensiveness & open source while enterprise ready offering and emphasis on reliability and bias evaluation. A top choice for AI developers and enterprises."
"Leading the Geometric Media Lab at ASU, I'm constantly exploring new methodologies in Generative AI and LLMs. RagaAI’s open source offering for LLMs and RAG Applications aligns seamlessly with our research and developer goals, offering a robust framework for evaluating complex AI systems. A must-have tool for any serious researcher and open source community." Views are personal & don't represent the organization.
Professor and Director at School of Arts, Media and Engineering, Arizona State University
“Having worked extensively in AI and LLMs, I recognize the significance of robust LLM evaluation tools. RagaAI Evaluation and Guardrail Suite for LLMs and RAG Applications is a key step forward with its comprehensiveness & open source while enterprise ready offering and emphasis on reliability and bias evaluation. A top choice for AI developers and enterprises."
"Leading the Geometric Media Lab at ASU, I'm constantly exploring new methodologies in Generative AI and LLMs. RagaAI’s open source offering for LLMs and RAG Applications aligns seamlessly with our research and developer goals, offering a robust framework for evaluating complex AI systems. A must-have tool for any serious researcher and open source community." Views are personal & don't represent the organization.
Professor and Director at School of Arts, Media and Engineering, Arizona State University
“Having worked extensively in AI and LLMs, I recognize the significance of robust LLM evaluation tools. RagaAI Evaluation and Guardrail Suite for LLMs and RAG Applications is a key step forward with its comprehensiveness & open source while enterprise ready offering and emphasis on reliability and bias evaluation. A top choice for AI developers and enterprises."
"Leading the Geometric Media Lab at ASU, I'm constantly exploring new methodologies in Generative AI and LLMs. RagaAI’s open source offering for LLMs and RAG Applications aligns seamlessly with our research and developer goals, offering a robust framework for evaluating complex AI systems. A must-have tool for any serious researcher and open source community." Views are personal & don't represent the organization.
Professor and Director at School of Arts, Media and Engineering, Arizona State University
“Having worked extensively in AI and LLMs, I recognize the significance of robust LLM evaluation tools. RagaAI Evaluation and Guardrail Suite for LLMs and RAG Applications is a key step forward with its comprehensiveness & open source while enterprise ready offering and emphasis on reliability and bias evaluation. A top choice for AI developers and enterprises."
"Leading the Geometric Media Lab at ASU, I'm constantly exploring new methodologies in Generative AI and LLMs. RagaAI’s open source offering for LLMs and RAG Applications aligns seamlessly with our research and developer goals, offering a robust framework for evaluating complex AI systems. A must-have tool for any serious researcher and open source community." Views are personal & don't represent the organization.
Professor and Director at School of Arts, Media and Engineering, Arizona State University
“Having worked extensively in AI and LLMs, I recognize the significance of robust LLM evaluation tools. RagaAI Evaluation and Guardrail Suite for LLMs and RAG Applications is a key step forward with its comprehensiveness & open source while enterprise ready offering and emphasis on reliability and bias evaluation. A top choice for AI developers and enterprises."
"Leading the Geometric Media Lab at ASU, I'm constantly exploring new methodologies in Generative AI and LLMs. RagaAI’s open source offering for LLMs and RAG Applications aligns seamlessly with our research and developer goals, offering a robust framework for evaluating complex AI systems. A must-have tool for any serious researcher and open source community." Views are personal & don't represent the organization.
Professor and Director at School of Arts, Media and Engineering, Arizona State University
“Having worked extensively in AI and LLMs, I recognize the significance of robust LLM evaluation tools. RagaAI Evaluation and Guardrail Suite for LLMs and RAG Applications is a key step forward with its comprehensiveness & open source while enterprise ready offering and emphasis on reliability and bias evaluation. A top choice for AI developers and enterprises."
"Leading the Geometric Media Lab at ASU, I'm constantly exploring new methodologies in Generative AI and LLMs. RagaAI’s open source offering for LLMs and RAG Applications aligns seamlessly with our research and developer goals, offering a robust framework for evaluating complex AI systems. A must-have tool for any serious researcher and open source community." Views are personal & don't represent the organization.
Professor and Director at School of Arts, Media and Engineering, Arizona State University
“Having worked extensively in AI and LLMs, I recognize the significance of robust LLM evaluation tools. RagaAI Evaluation and Guardrail Suite for LLMs and RAG Applications is a key step forward with its comprehensiveness & open source while enterprise ready offering and emphasis on reliability and bias evaluation. A top choice for AI developers and enterprises."
"Leading the Geometric Media Lab at ASU, I'm constantly exploring new methodologies in Generative AI and LLMs. RagaAI’s open source offering for LLMs and RAG Applications aligns seamlessly with our research and developer goals, offering a robust framework for evaluating complex AI systems. A must-have tool for any serious researcher and open source community." Views are personal & don't represent the organization.
Professor and Director at School of Arts, Media and Engineering, Arizona State University
Recommended Resources
