AI Observability tailored to your Industry

Build transparent credit scoring models and explain every score prediction to customers

Explain credit risks to internal stakeholders before penalizing customers

Continuously monitor credit scoring models for performance, drift, bias, and quality issues

Detect anomalous model behavior at its onset to prevent major risks to data exposure

Understand the root cause behind model faults and instantly launch recovery plans

Reduce time-to-resolve issues and consequently solution downtime

Continuously and automatically monitor if NLP models are performing as expected

Track subtle drifts in customer responses and detect the root cause for such behavior

Increase successful customer engagement with consistent NLP performance

Detect suspicious activities and subtle anomalies with continuous automated monitoring

Understand the root cause behind issues flagged by Censius monitors

Maintain consistent performance and ROI over pre-defined thresholds

Detect subtle changes in input patterns for computer vision solutions used in claim routing

Instantly flag issues when image data shows signs of poor quality or drift

Explain model predictions for critical data points to customers and internal stakeholders

Use intuitive dashboards and analysis widgets to explain why certain offers work better together

Explain poor performance of specific offers to business teams and other stakeholders

Instantly catch drifting customer behavior to design offers accordingly

Continuously and automatically monitor if computer vision solutions are correctly capturing documents

Detect drifts in document patterns and drop in data quality

Maintain high accuracy for sensitive documents with cohort monitoring tools

Track the performance of health trackers to maintain stability in detection or prediction methods

Pin down the root cause behind predictions and alerts sent by the health monitors

Analyze and report analysis results with flexible dashboards and widgets

Continuously and automatically monitor if NLP models are performing as expected

Track subtle drifts in patient’s responses or medical data and detect the root cause behind them

Improve patient consultations and engagement with consistent NLP performance

Manufacturing machinery is sensitive and monitoring makes AI in manufacturing more reliable

Detect root cause behind issues in record time and reduce downtime

Increase transparency of autonomous model with explainable AI

Increase data reliability with continuous and automated data quality and drift monitoring

Monitor input and output of IoT devices and flag subtle abruptions early on

Explain model learnings such as preferred light intensity or temperature to end-users

Ensure high sensitivity and precision of predictive maintenance models with continuous monitoring

Instantly understand the why behind every prediction to validate them before expensive repairs

Plan maintenance activities in advance based on consistently tracked drift patterns

Ensure high returns from reliable predictions on campaigns

Understand the specific causes behind campaign failure or success

Continuously monitor customer data to detect subtle drifts in behavior or buying patterns

Monitor to save cost with reliable restocking and sales predictions

Explain budget plans to supervisors or management with explainable AI

Increase model transparency by building and sharing monitoring reports with all stakeholders

Continuously and automatically monitor if NLP models are performing as expected

Track subtle drifts in customer’s responses or purchase data and detect the root cause behind them

Improve customer engagement with consistent NLP performance and quick adaptability

Continuously monitor the trustworthiness of AI-based grading with minimal resources

Explain AI decisions on grades to students and guardians with high clarity

Resolve issues in record time before the model can have any major impact on students

Monitor the predictive capability of recommender systems built for targeted learning

Explain personalised recommendations and the specific benefits of the curriculum

Instantly catch drifts in student’s learning patterns or reception of recommendations

Monitor performance of report generation and communication pipelines

Maintain personalized and frequent engagement with guardians through continuously monitored NLP

Redirect employee efforts towards more strategic tasks by automating monitoring activities