TECHNOLOGY

INTRODUCING the metacognitive ai platform (MAP)

MAP is a ML model optimisation and monitoring platform that provides a reliable, transparent view of AI decision making processes. Mitigating real-world uncertainties and biases​, providing performance troubleshooting in real-time​, facilitating collaboration, AI adaption, trust to deploy, and continuously improving performance.

When current AI models fail, operators remain unaware of the problem until it’s too late. Thanks to Metacognitive’s feedback loop, operators are notified of negative outcomes before they occur and given the tools to refine their models for the future, leading to improved accuracy and better performance.

data management,
explainability &
troubleshooting

AUTOMATed alert system & personalised rEPORTING

UNCERTAINTY QUANTIFICATION & adaptive feedback

INTRODUCING the metacognitive ai platform (MAP)

MAP is a ML model optimisation and monitoring platform that provides a reliable, transparent view of AI decision making processes. Mitigating real-world uncertainties and biases​, providing performance troubleshooting in real-time​, facilitating collaboration, AI adaption, trust to deploy, and continuously improving performance.

When current AI models fail, operators remain unaware of the problem until it’s too late. Thanks to Metacognitive’s feedback loop, operators are notified of negative outcomes before they occur and given the tools to refine their models for the future, leading to improved accuracy and better performance.

data management, explainability &
troubleshooting

AUTOMATed alert system & personalised rEPORTING

UNCERTAINTY QUANTIFICATION & adaptive feedback

metacognitive reveals the true capability of your ml model

uncertainty quantification

EXPLAINABILITY AND DRIFT DETECTION

Metacognitive turns Black Box AI into an understandable transparent decision process users can access. It explains drifts in input data and model results. If an ML model starts to become less accurate, Metacognitive alerts operators.

UNCERTAINTY QUANTIFICATION

Metacognitive is the only tool that re-evaluates accuracy values after training and provides all possible ML predictions in real-time for enhanced performance, more reliable decisions, and debugging data and model bias.

predictive personalisation feedback

predictive personalisation feedback

Metacognitive actively detects concept drift and produces reports to show why it’s happening and what needs to be fixed. Customer profiling allows Metacognitive users to customise the reports they receive to suit the technological background of different stakeholders. Whether you need semantics and statistics, or data and details, Metacognitive ensures incomprehensible Black Box AI becomes a thing of the past.

ADAPTIVE FEEDBACK

ADVANCED REASONING

Metacognitive combines the above pillars to provide understandable explanations of AI decisions for all users. It models uncertainty to give more insights into what causes it. Fairness and AI ethics analysis are made much reliable with this level of rationalization.

MODEL PERFORMANCE TROUBLESHOOTING

Using patentable technology, an all-encompassing approach to derive meta insights that assess ML models from their operating domain weaknesses, predicting and preventing underperformance, instability, and downtimes.

USER ADAPTATION OF AI

Metacognitive incorporates human decisions, intentions and sentiments into AI decisions: a) to truly understand human inputs, b) to enable collaboration, and c) to respond reliably. Through advanced techniques (e.g., reinforcement learning), users can customize and collaborate even with large model responses easily.

Key features

Drift detection

Stop model failure before it happens. If your ML model starts to become less accurate over time, Metacognitive will let you know.

Explainability

Understand what your ML model is doing and why. Metacognitive turns Black Box AI into an understandable transparent decision process you can access.

Uncertainty quantification

Metacognitive is the only tool that re-evaluates accuracy values after training and provides all possible future ML predictions for debugging and enhanced performance.

Predictive personalisation feedback

Proactively forecast drift before it happens, and get alerts to notify you if your data is no longer fit for purpose. Enjoy better team collaboration with reports you can customise to suit different stakeholder needs.

Adaptive feedback

Receive auto-generated reports with recommendations to improve model performance. Use these insights to plug-in specific analytics into your ML pipeline and improve user experience in real-time.

contact us

We’re happy to answer any questions you might have.