AI Application Development

AI Suite

What Differentiates Us?
AI Use Cases Development Expertise
Innovative QX AI Framework

QX AI Architecture
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Execution Framework

The number one mistake in data science is working on a wrong problem, which generates little or no business value. Return of investment (ROI) applies to every part of business and AI application is no exception too. That is why we start with identifying the right business use cases for your business. Our team has lots of experience in delivering AI solutions to transform business across many fields in the industry. We will make sure your investment is on the right ones.

Second, we will come up with measuring criteria of the solution to be able to quantify the ROI.

Third, data exploration is a necessary and important step. Every company has different data maturity and quality even within the same field. We make sure we truly understand your data and unique business rules applicable to your business before feeding into the model.

Furthermore, we also integrate relevant numerous data external sources to mine new correlations with your data and discover new insights you could not find.

Next critical step in building the AI application is feature engineering. Traditionally, features are built in an ad-hoc way and not reused from one solution to another. In our architecture, we make sure features are stored in a feature warehouse, so that they can be leveraged to support all AI solutions.

We also pre-built features for every industry based on our previous experience and keep adding the new ones from new learnings. This largely accelerates the development cycle. Models will be trained with multiple state-of-the-art algorithms including xgboost, random forest, deep neural network, with the proper cross-validation and parameter selection. This process is fully automated to achieve the most efficiency. Thereafter, models will be deployed using our AI platform easily on either Azure or AWS, with a streamlined process. Once the model is in production, we will start monitor the model performance and possible data drifting.

Alerts will be set up to track any abnormality. A retraining process of a model will happen if we find the model performance goes beyond the pre-set threshold.

Finally, and most importantly, business impact is always measured to obtain the ROI. This process is repetitive, and we make sure that your business gets more and more value as the solutions are getting refined and improved.

In summary, our AI Model Architecture, technologies, and methods can rewrite the dynamics of business, improve bottom-line, and enhance business models that can multiply revenue with a minimal incremental cost and propel organizations to accelerate their digital transformation journey. More importantly, with our framework and guaranteed speed to market, you no longer need to wait for months before you can see the business impact.

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