Welcome to 2023! The last year was full of improvements and new features, as you can read about in our post:
We plan many new exciting releases and updates in the year to come.
In this post, we present an updated Roadmap for all AIMMS products, as well as a view to our approach in prioritizing our work.
The Product Roadmap is driven by our Product Strategy team’s vision. We always look to the future of available technologies, the needs of the market, and the needs of our current users.
We do our best to give users multiple feedback channels to help us prioritize work that will help you the most. The Ideas section of this community platform is a one of those, along with individual sessions with customers, feedback forms and surveys, and a few others.
We focus our development work on improving and innovating in the following areas:
🌐Supply Chain Apps
Our off-the-shelf supply chain apps, built on the power of our development platform and deployment services.
This year we will release new versions of the apps, extending the functionality from strategic planning to include tactical planning, easing the input data preparation and improving the user interface, both for first-time users and for ‘regulars’.
User Interface and beyond. High-level goals are to stimulate end-user adoption and ease result interpretation.
This year we anticipate further visualization improvements, workflow-support extensions and more.
Reduce time and energy spent by model developer on preparing input data, using the full power of data science. We are still exploring how best to help app developers and end users in this aspect, but intend to release some first enhancements this year.
Think of topics such as automated data ingress, data inspection, cleansing and repair, extend capabilities for data analysis.
How does AIMMS work with your ecosystem of tools. Work with current integration standards.
This year we plan to add various forms of database support to our Data Exchange Library (DEX), easier use of Python and R and exposing Azure services.
Algorithmic capabilities, and tools to help you improve your model. To handle the ever-growing complexity of models and data-size.
This year we will work on tools to help explain results, starting with ways to help users resolve infeasibility.