Implementation services for building & optimizing evaluation pipelines

Bring your Gen AI evaluation process to the next level with Rhesis AI’s implementation services. We specialize in building evaluation pipelines from scratch or improving existing ones, leveraging a deep understanding of state-of-the-art frameworks, tools, and best practices to deliver robust, efficient, and scalable testing pipelines.
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Expertise in Gen AI evaluation & testing pipelines

Transform your Gen AI validation process with Rhesis AI’s implementation services. We focus on aligning with your evaluation objectives and addressing your current challenges to create effective and reliable testing workflows.
Our approach begins by analyzing and optimizing your existing evaluation pipelines or setting up new ones tailored to your operational and technical needs. We support every aspect of the process, including test case generation, test metrics creation, and evaluator selection.Our team has extensive experience working with frameworks like Promptflow, DeepEval, and RAGAS for comprehensive testing and evaluation. We integrate cutting-edge tools to ensure that every aspect of your evaluation process is tailored to your specific needs.
We employ advanced CI/CD methodologies to streamline testing pipelines, utilizing platforms like MLflow for experiment tracking, langfuse for observability, and Docker and Kubernetes for containerized deployment.
Tailored Pipelines for Gen AI Testing
We develop pipelines that accommodate various testing scenarios, including adversarial testing and robustness validation, and create detailed metrics tailored to your use cases, leveraging tailor-made domain-specific benchmarks.
Test Case and Metrics Creation
Our team specializes in designing metrics that are aligned with your concrete business objectives, ensuring comprehensive and meaningful evaluations, while making use of frameworks like DeepEval and RAGAS, ensuring comprehensive and meaningful evaluations, going beyond groundedness and relevance.
Framework and Tool Integration
Our expertise includes setting up CI/CD pipelines in your orchestration tool of choice, e.g., GitHub Actions, Azure DevOps, Jenkins, or TeamCity, integrating industry-leading tools and frameworks. These integrations are designed to provide consistent, scalable, and efficient testing environments.
End-to-End Pipeline Optimization
We build scalable infrastructures that accommodate the growing demands of LLM applications by using containerization with Docker and orchestration with Kubernetes. Our pipelines incorporate automated test execution platforms, enabling consistent and repeatable testing without manual intervention.
Industry-Specific Testing Expertise
We address unique testing needs across industries like finance, insurance, and e-commerce, tailoring solutions to match sector-specific challenges. We emphasize scalable and adaptive systems that enhance customer interactions with predictability and fairness.
Scalable and Future-Ready Solutions
By implementing frameworks that are both robust and flexible, we ensure that your testing capabilities remain ahead of the curve. Our expertise in MLOps/LLMOps ensures seamless updates and ongoing optimizations as your needs grow or change.
TEST STRATEGY

Gen AI test coverage planning

For teams looking to establish a comprehensive test strategy, our implementation service delivers a detailed test coverage plan tailored specifically to Gen AI applications.
Test Coverage Planning: We design a test matrix that delineates the critical components to test, ensuring extensive coverage across use cases, functional requirements, edge cases, and personas while minimizing blind spots. The matrix is enriched with tools like RAGAS and DeepEval for automated validation and metric tracking.
Gen AI vs. Traditional Testing: Recognizing the challenges posed by Gen AI’s non-deterministic behavior, we implement strategies such as statistical benchmarking and output distribution analysis to adapt and extend traditional test paradigms to Gen AI systems.
Frameworks: Our approach incorporates industry-standard frameworks such as MITRE’s ATLAS for adversarial testing and OWASP guidelines for application security, integrating them with tools like RAGAS and DeepEval to ensure your test coverage adheres to best practices while meeting the demands of modern Gen AI systems.
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TEST SCOPE

Custom & advanced test scenario generation

For teams aiming to ensure comprehensive evaluation of their Gen AI applications, we provide services to design and implement tailored test cases.
Custom test set generation: Collaborate with us to create customized test scenarios addressing your application’s unique needs, leveraging tools like the Rhesis Test Bench to define edge cases, handle uncommon inputs, and assess use-case specific performance benchmarks.
Adversarial and robustness testing:  Utilize advanced methodologies, including industry-benchmarks, adversarial attacks and perturbation testing, to identify vulnerabilities and evaluate robustness against unpredictable inputs.
Compliance and ethical validation: Extend testing beyond functional requirements by crafting test cases focused on ethical considerations, such as bias detection and fairness, incorporating tools like RAGAS and Prompflow.
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TEST INFRASTRUCTURE

Evaluation pipeline setup

For teams looking to establish a reliable and efficient testing infrastructure, our implementation service sets up the core components for automated testing in Gen AI applications, ensuring that your pipeline can handle the intricacies of Gen AI while aligning with industry standards and best practices.
CI/CD Pipeline Integration: We design and implement robust CI/CD pipelines using tools like Jenkins, GitLab CI, to ensure continuous integration and delivery, as well as Prefect to automate test execution, enabling faster iterations and more reliable testing processes.
Automated Test Execution: We configure automated test execution platforms, utilizing technologies such as Docker for containerization and Kubernetes for orchestration, to enable consistent and repeatable testing without manual intervention.
Scalable Infrastructure: Our team builds a flexible and scalable infrastructure using cloud solutions (AWS, GCP, or Azure) and containerization with Docker to accommodate the increasing demands of Gen AI testing. The infrastructure is designed to evolve with your project needs.
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ITERATIVE IMPROVEMENTS

Optimizing applications for production readiness

For teams preparing Gen AI applications for deployment, we focus on refining and improving workflows to ensure production-quality performance. This service ensures your Gen AI applications meet production standards with confidence, combining efficiency, reliability, and adaptability in testing.
Test Result Analysis and Reporting: Work closely with your team to analyze test outcomes, evaluate application readiness, and provide actionable feedback for continuous improvement.
Implementing Industry Best Practices:  We introduce and integrate proven methodologies such as MLOps/LLMOps for model lifecycle management, ensuring that tests are efficient, repeatable, and scalable.
Automated Testing and Adaptability: We establish automated testing workflows using tools like Prefect or Airflow for orchestration and GitHub Actions, GitLab CI for continuous integration, allowing seamless updates and ensuring that evaluation processes remain robust.
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OFFERING

Why choose Rhesis AI implementation services?

Get hands-on experience and expert guidance to tackle the unique challenges of Gen AI testing, ensuring your team is equipped with practical skills and actionable strategies. Our services are designed to meet your team’s needs—whether you prefer the convenience of online sessions or the hands-on interaction onsite.

Streamlined Integration

We bridge the gap between development and production by implementing tailored testing pipelines that integrate seamlessly into your existing workflows. Leveraging technologies like Docker and Kubernetes, our implementation services ensure minimal disruption, enabling faster deployment and efficient scaling. Whether enhancing current processes or building from scratch, we align our work with your operational needs, using CI/CD tools like GitHub Actions, GitLab CI or Jenkins, to deliver measurable value quickly and optimize your time-to-market.

Framework Agnostic

We leverage a wide array of frameworks and the best tools available for Gen AI evaluation, ensuring that your solution is tailored to your specific needs. Whether integrating tools like DeepEval for LLM testing or using RAGAS for retrieval-augmented generation systems, our flexible approach ensures that your testing capabilities remain adaptable, robust, and future-ready, even as your requirements change with emerging technologies and market trends.
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Industry-Specific

We specialize in tackling the unique implementation challenges faced by industries such as finance, insurance, and e-commerce. In finance, we focus on reducing risks and ensuring regulatory adherence. For insurers, our services address the need for unbiased claim processing systems. In e-commerce, we emphasize creating accurate, fair customer interactions. By tailoring our services to your sector’s requirements, we help you achieve operational excellence and regulatory compliance.

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