Redapt | Operations
- Business Transformation
- Cloud Engineering
- Cloud Native
- Artificial Intelligence (AI)
- Modern Datacenter
- Emerging Tech
- IoT and Edge
- Advanced Analytics
- Google Cloud
- Hybrid Cloud Implementation
- Google Anthos
- Systems Integration
- Application Development
- Application Modernization
- Machine Learning
With more and more enterprises looking to adopt containers and Kubernetes in order to accelerate their development process, one question we often hear from clients is: How do we get started?
As enterprises dive into AI adoption, it is critical that they understand industry trends. The recent Forbes article, Top Artificial Intelligence (AI) Predictions for 2020 from IDC and Forrester...
From automation and data analysis, to internal communications and customer service, there’s a lot of power in Artificial Intelligence (AI).
With many enterprises looking to change the way they use technology in response to increasing competition and expectations, accelerating the delivery of high-quality products is critical.
Artificial Intelligence (AI) has graduated from buzzword to technical reality. For many enterprises, however, large hurdles remain in actually adopting AI into their businesses.
By some estimates, close to 90% of Machine Learning (ML) projects developed by data scientists fail. This translates into wasted resources and the potential of ML being deployed at a snail’s pace.
It used to be that working on monolithic applications was a tedious process, vulnerable to catastrophic crashes that made an entire application inoperable for an extended period of time.
Building out your datacenter is about more than simply doing rack and stack. Without having a firm grasp of your needs, you risk blindly throwing money at the project and the very real potential...
At Redapt, we try to remain relatively tech agnostic. Every client we work with has specific needs, and those needs often require an array of technical skills, infrastructure, and tools.
Modern datacenters provide companies with the flexibility and capacity they need to effectively utilize the sheer amount of data being produced every day.
Making an investment in modernizing data...