A company dealing with deploying a new AI model, is facing challenges in improving the performance and reliability of the model and lacks the expertise to do this?
Benchmarking - the company is having difficulty improving the performance of the model based on the dataset they have collected.
Datasets - The company is unable to identify which scenarios they have not considered when training their models.
Robustness - why does the model keep failing when it is deployed to production?
Advai's system identifies where models are weakest and which areas in training datasets are most un-robust or un-balanced.
Our expert researchers can help identify the best features to augment you model with to improve the performance and help implement optimal strategies to improve performance.
By being able to train the teams on common issues with model robustness, the Advai team can help with long term management of AI models in production environments.
By understanding the gaps in the training data it became possible to improve the performance of the model for specific scenarios experienced in production.
An optimal model implementation was chosen which incorporated all key parameters required by the business, and this comparison was able to be done across multiple model choices recommended by the Advai team.
Because the customer knows which parts of their AI models perform well or poorly, they can better manage the deployment in production and ongoing support, thanks to Advai consulting.