Observability Hub
Empower your AI/ML workflows with Metricwise's Observability Hub, a comprehensive suite designed to bring transparency, reliability, and accountability to every stage of your AI models. Our platform offers deep insights into model behavior, detection of biases and drifts, and benchmarks performance against industry standards. With customizable features and intuitive tools, Metricwise’s Observability Hub helps organizations foster trust and achieve optimal results.
Get started for free
Dynamic Bias & Drift Detection
Maintain fairness and reliability across the model lifecycle with real-time bias and drift detection.
Identify and mitigate biases or drifts as they occur, ensuring models remain fair and aligned with intended outcomes.- Address potential discrepancies caused by data shifts or evolving inputs, preserving model accuracy and equity.
- Real-time alerts enable quick intervention, allowing teams to safeguard model integrity and adherence to regulatory standards.
Holistic Benchmarking
Evaluate model performance through comprehensive benchmarking tools that provide actionable insights for continuous improvement.
- Benchmark your models against a wide range of industry standards and proprietary benchmarks to understand their strengths and areas for enhancement.
- Gain an external perspective on model performance to drive targeted improvements and stay competitive.
- Track improvements over time and ensure models meet or exceed critical performance thresholds.
Adversarial Monitoring
Safeguard the integrity of your text-based models by evaluating their performance under adversarial conditions..
- Continuously monitor model performance before and after adversarial interactions, identifying vulnerabilities and performance gaps.
- View breakdowns of each attack method impact on model performance, supporting a holistic understanding of resilience..
- Capture and analyze detailed metrics that reveal the impact of adversarial inputs, enabling proactive mitigation strategies.
- Improve model resilience by addressing performance weaknesses that emerge under attack conditions.
Interactive Model Profiling
Conduct in-depth analyses of model performance with interactive profiling tools.
- Access detailed performance metrics, feature importance data, and prediction accuracy insights for a comprehensive view of model behavior.
- Customize profiling views to focus on specific metrics and gain insights into how individual features impact overall model predictions.
- Use intuitive visualization tools to detect patterns, identify areas for improvement, and support informed optimization decisions.
LLM Assessment & Tracing
Ensure large language models (LLMs) meet high standards of contextual relevance, accuracy, and safety.
- Assess LLMs on multiple criteria, including contextual precision, recall, answer relevancy, knowledge retention, summarization quality, and toxicity levels.
- Detect and address issues like bias, hallucinations, and faithfulness to intended outputs, ensuring safe and reliable LLM performance.
- Enable trace analysis for full oversight, documenting model interactions to maintain accountability and support troubleshooting efforts..
Observability Hub
With Metricwise Observability Hub, organizations can ensure that their AI models are transparent, reliable, and aligned with industry
standards. By providing actionable insights, bias detection, and explainability tools, Metricwise helps build trust in AI systems,
empowering enterprises to achieve fair, accountable, and high-performing AI solutions.
