Mona's Intelligent Monitoring Solutions

As a highly extensible solution, Mona’s intelligent monitoring platform is suited for a variety of use cases including traditional machine learning, LLMs, NLU, NLP, generative, chatbots, computer vision, speech, audio, and robotic process automations (RPA).

Machine Learning (ML)
NLU, NLP & Chatbots
Computer Vision
Speech / Audio
Intelligent Automations

Monitoring for Machine Learning (ML)

Mona enables teams to continuously collect, transform, and analyze data from all parts of the AI system, providing actionable insights for data science and machine learning teams.


ml monitoring insights
  • Proactively detect drifts, outliers, and other unexpected behavior in your inputs and predictions

  • Define and track custom metrics based on varying business cycles and outcome/feedback availability

  • Optimize MLOps by quickly resolving critical issues and iterating on new model versions 

Example use cases: Works for any AI use case, including fraud detection, LTV prediction, credit risk, market segmentation, churn prediction, ads recommendations and more


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Monitoring for LLMs, NLP, NLU & Chatbots

Mona provides engineering and data teams with actionable insights into issues with their language models or chatbots, ensuring they are fully optimized to support your business needs.

monitoring nlu nlp chatbots


  • Mona can monitor any NLP / NLU use case including intent identification, category classification, entity extraction, and language detection

  • Track and get alerted on a variety of algorithmic KPIs, such as confidence scores and output class distributions, correlations with user responses, and more

  • Whether your system is based on a knowledge graph, a ML model, or any other algorithm, Mona detects performance issues even when they are occurring only for a specific text source, customer, or any other business segmentation

  • Monitor systems built completely in-house, existing solutions built by vendors or hybrid systems

Example use cases: Intent Identification; Category Classification; Entity Extraction; Language Detection


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Monitoring for Computer Vision Systems

Mona instantly detects any issues that arise with computer vision systems, alerting data science teams on exactly where the issues occur and how to resolve them.


computer vision ai monitoring
  • Monitor your specific vision-based AI use case including image classification, object detection and recognition, video motion analysis, and OCR 

  • Track RoI dimensions, classifier confidences, output distributions and correlation with manual labeling. Use Mona to track both out-of-the-box and your own custom metrics

  • Detect issues even when those occur only for specific camera models, image quality classes, file formats or other business/data segmentations

  • Monitor systems built completely in-house, existing solutions built by vendors or hybrid systems

Example use cases: Image Classification; Object Detection; Object Recognition; Video Motion Analysis; OCR


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Monitoring for Speech / Audio Based AI

Mona automatically detects if there is an issue with audio and speech related models and algorithms, ensuring fast and reliable fixes so businesses are not negatively impacted.

speech audio ai monitoring
  • Monitor your speech and audio based AI use cases including speech-to-text, language detection, voice recognition and more

  • Track your speech-to-text and consequenting text-based models in the same context, immediately identifying if the issues originate in the textual analysis or in the preceding audio analysis

  • Get instantly notified when issues arise in specific segments of your data, such as changes in recording hardware or an end-user environment

  • Monitor systems built completely in-house, existing solutions built by vendors or hybrid systems

Example use cases: Voice Analytics; Speech-to-Text; Language Detection; Voice Recognition


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Monitoring for Intelligent Automations

Mona automatically surfaces production issues within automations and data-driven workflows to reduce business risk and accelerate time to resolution for RPA developers and production support teams.


monitoring intelligent automations


  • Increase automation completion rates
  • Reduce number of support tickets
  • Reduce time to issue resolution

Example use cases: Robotic Process Automation (RPA); Intelligent Process Automation


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Questions About Your Use Case?