Detect and Remove AI Biases and Hallucinations to Deliver Trustworthy Outcomes
Enhops Gen AI Testing and Evaluation Services boost your AI application's performance & accuracy. With extendable architecture, contextual intelligence, and tools like prompt builders, our solutions are built on Azure's native data estate for a robust testing environment.
Our deep expertise in automation ensures Language Models are tested with high accuracy, reliability, and integrated with CI-CD pipelines. We prioritize responsible AI, adhering to Helpful, Honest, Harmless (HHH) principles and safeguarding data.
Understand
Customer Challenges
and Requirements
Data
Understanding
and Preparation
Synthetic
Dataset Generation
Manual and
Automated Prompt
Categorization
Configurable
Generator LLM and
Critic LLM
Evaluation
Metrics and Testing
Methodologies
Comprehensive
Test Reporting
Test Automation
Integration in CI/CD
Feedback and
Training
Continuous Learning
and Optimization
Customized testing frameworks & methodologies to meet specific client needs and use cases.
Includes various metrics like performance accuracy, robustness, and ethical considerations.
Tailored solutions for evolving enterprise needs, seamlessly integrating with workflows & AI frameworks.
Makes testing accessible and faster, even for non-technical users.
Extensive experience in software testing, data management, and custom AI solutions.
Targeted evaluation and iterative testing of language models and RAG systems.
At our core, we leverage automation to address quality challenges, including those in Gen AI applications. Drawing on our parent company's (ProArch) expertise, we guide you toward tailored AI solutions that deliver the results you need.
Testing generative AI applications is inherently more complex than traditional testing methods. While conventional approaches involve clear functional and non-functional testing parameters, generative AI demands unique strategies tailored to its intricacies. To effectively assess these applications, several innovative techniques are employed like Synthetic Test Datasets, Benchmarking Against Ground Truth, Evaluation Metrics, and more.
Some Common metrics include Faithfulness, Relevance, Context Precision, Recall, Hallucination Rate, Bias, Toxicity, and ethical fairness.
Enhops offers a robust framework for testing that encompasses benchmarking, observability, and metric analysis across AI models to guarantee quality, performance, and fairness. Our ready-to-use accelerator provides clients with a head start in testing their generative AI applications, significantly reducing time to market and ensuring seamless application performance.
Yes, our Gen AI testing solutions are highly customizable and can seamlessly integrate with your current MLOps pipelines or other AI workflows.
Besides AI testing, Enhops offers services like software performance testing, functional testing, security assessments, and DevOps consulting to support end-to-end digital transformation.
