When you have a business based on a vision of the future, rather than the present, understand that the majority of your critics will likely be looking from the perspective of the present.
Older, larger, organizations approach discontinuous innovation with more trepidation whereas companies like Cadre do so continuously, routinely, and more confidently.
Therefore, this changes the business model - it is a process.
Cadre is built upon our process as much as our technology. This collaborative effort strives for flawless execution during implementation. Results come from committing to a digital transformation focused on impact, speed, and scale. Our proven performance process is about value-driven success.
Our process ↓
Discover
Beginning of the process, identify the opportunities, problems, desired future state, and value of the solution.
This is where we get to work unlocking the value a transformation will provide. During this stage we identify the initial problem set, consult on an approach, build a prototype, carve a path forward, and identify the value it will bring. Once we agree on terms, we get to work.
Collect
Review currently available data/inputs, identify new data points needed, and outline/scale collection efforts.
This is where we start compiling data. We begin not only making your data smart, but automating it as well. We’ll organize, curate, and catalog data setting you up for long-term success and value. This is one of the most important parts of the process.
Integrate
Integrate existing and new data, model building, transferring to the process of your core business.
This is where the magic begins to happen. Cadre begins to build models according to your strategy and automation comes alive.
Recall
Modifications, retraining, testing, and continued integration.
Often referred to as wash, rinse, repeat, this is the repeat cycle. We’re going to iterate the process, find anomalies in the models, fix and retrain for maximum accuracy. This is another very important part of the overall process and where others fall short.
Logic
Accuracy review, result review, automated decision making adjustments and continuous data cycling.
This is where we’re going to begin seeing results from the previous steps. In Logic, you’ll begin to see the process deliver real-time results. These results derive the value from the Discovery process. Logic analytics drive decisions for solving the next set of problems.
Insight
Dashboard data and analytics reside. Items such as run time, CPU/GPU/TPU usage, general performance.
Insight is the window into the whole process. This real-time display of newly developed models provides the analytics of what you’ve invested in; Value. Insight is the constant measurement and feedback loop of ongoing value delivered from this process of artificial intelligence transformation.