What your organization needs to find success with artificial intelligence (AI) depends largely on two things: where you start and what level of support you receive during implementation. Trying to do too much at the beginning, or attempting to adopt new AI techniques such as machine learning (ML) without the proper expertise, are recipes for failure.
Here's how Redapt's ML Accelerator can help you implement AI and ML successfully.
The challenges of implementing ML at scale
The amount of data in the world is unprecedented. And organizations like yours need powerful tools to make sense of all the data.
That's where ML comes in. With the right tools to digest and analyze the stream of data, leaders can make data-driven decisions to propel their organization forward.
ML promises to transform a business by teasing apart the relationship between data points. This helps organizations uncover and act upon insights.
While the promise is real, many ML models wind up never leaving the lab due to challenges getting them to production. These problems arise because the lab is much different than production. Production is operated by IT, who often rely on traditional processes that were built for legacy systems and aren't able to scale quickly or at an optimal price point.
Redapt’s ML Accelerator package removes hurdles with development, such as legacy hardware. It also offers powerful algorithms at an optimal price point.
3 steps to machine learning success
Redapt's accelerator delivers ML that scales as needed to increase agility and enhance operational efficiency. It lays the critical groundwork for successful AI adoption in a matter of months.
It's a wiser choice than jumping in feet first, which is more likely to result in failure with your AI initiative. Here's how to use Redapt's ML Accelerator package to find success with AI.
Step 1: Partner with Redapt
Before organizations can find success with AI, they must modernize their applications and datacenters.
Our ML Accelerator lays the critical groundwork for successful AI adoption in a matter of months by modernizing an organization's resources. It also mitigates risk associated with ML because it's built with best practices in mind.
Step 2: Accelerate AI adoption
While our consultants get everything up and running for your business, we are also here to help your organization adopt AI quickly.
We can talk about powerful use cases, help you identify a good first project, or provide training to team members. This service is tailored to the individual needs of each organization, so trust that we are here to help you have a successful launch.
Step 3: Launch and evaluate
Our infrastructure is ready to use when it arrives at your datacenter and experienced consultants are standing by to solve any challenges that arise. This way, your business can move from zero to production ready on a rapid timeline.
It's time to launch your first model to production and experience the benefits of ML. During this phase, evaluation is key. See what happens, measure results, and keep moving forward.
Whether your organization is just starting to think about AI, moving into production, or operating at scale, it can help to talk things out with a supportive partner.
Learn more about applying AI to your business intelligence. Download our free eBook, The CIO’s Guide to Leveraging AI to Leap Ahead of the Market.
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