Enabling AI to Predict Project Success

by | Apr 2, 2024 | IMPACT | 0 comments

Enabling AI to predict project success

The current landscape of technology has been greatly affected by the rise of neural networks or machine learning as computers become more and more powerful, a progression in line with Moore’s Law.

At Mykongsi, we are also eager to incorporate AI/ML into our own product offerings, recognizing that this convergence of technology and intelligence helps us provide better technology solutions.

Being in the enterprise software development for more than 20 years, we find that one of the hardest parts of the software development industry is in Project Estimation, thus this is where we focus our AI/ML first.

Our IMPACT App, at its core is a task management system, where we train our model based on historical completed projects and tasks. Based on this, whenever you create new projects, you can utilise our trained models to see how well the project will progress over time, and whether it can meet your expected deadlines. We believe this can help not only project managers, but also anyone who is involved, giving everyone the same view on the project’s status. Now, truly every one can be a project manager!

Coming up with this model was not always rainbows and butterflies. Like developing any other AI models from the ground-up, we too were faced with challenges in getting enough data to feed into our model, as we are building a custom AI model that uses inputs from our app. With the help of certain open-sourced project management data and substantial data normalisations, we now have good enough data for model training.

We are also collaborating with an international university to research, validate, and speed-tune the first version of our project success prediction model.

All in all, we are glad that we can come up with this model, and hope people will find a good use for this feature alongside other awesome stuff that we developed in the app.

Hope you would try it out and give us your feedback!

#BetterEveryDay

 

 

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