Deploying AI models

Deploying AI models may be perceived as the final step in the process of becoming an AI-powered enterprise. Get your data holdings structured properly, turn business challenges into data science problems, and deploy the perfect AI model to transform your business.

However, this is not the end of AI implementation. In some ways, AI deployment is just the beginning.

Long-term maintenance should be part of the deployment process for your AI solution to work for your business. Without constant monitoring and tuning, all models lose accuracy. This is because it will not be able to accommodate changes or growth in the data used in the model.

The Importance of Monitoring and Coordination

One typical example is the medical case.

AI models are currently being used to determine medical data such as mammogram images that detect breast cancer. Models may also be developed using up-to-date medical data from a set of patients. The medical data of these patients will be updated in the following years. Some remain healthy, while others develop cancer. Some are in remission, others have recurrences of previous illnesses, and so on.

If the model is not supervised and adjusted to incorporate this new data, its AI accuracy will degrade.

Toward realization of monitoring and coordination

Such complex monitoring and coordination is essential, but also extremely difficult to achieve. The best bet for this problem is a hybrid approach that includes:

1. Performance monitoring dashboard to monitor various aspects of the solution
2. A team of validators and adjusters who make adjustments as needed and evaluate their effectiveness

This is not an easy task to achieve. Many companies lack resources to maintain the number of employees with the necessary skills to perform this monitoring and coordination in-house.

This is where CrowdANALYTIX(CrowdANALYTIX) AI implementation service companies like are useful. CrowdANALYTIX leverages crowdsourcing to deploy customized AI models, as well as monitor and adjust them with high accuracy over time. This saves money and maintains efficiency over time.

AI implementation does not end with deployment. Maintenance should also be included.

Please feel free to contact us if you are interested.

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Source:https://www.crowdanalytix.com/deploying-and-maintaining-production-ready-models/
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