Machine Learning and AI

Science fiction likely comes to mind when thinking about machine learning (ML) and artificial intelligence (AI). In reality, the opportunities and benefits of ML and AI are more critical to our lives than we would have ever imagined. Businesses are already using these technologies to make better forecasts, provide helpful product recommendations, manage maintenance schedules to prevent breakdowns, and identify anomalies.

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Scale your Business Quickly with Machine Learning

Machine learning is making a significant impact across various industries, improving their agility and efficiency. It’s important to point out that ML and AI cloud services are not the same; ML is the engine behind AI. Taking advantage of machine learning requires a lot of data and specialized compute power to train and run models on all of the data. The more data you have, the better the probability of likely outcomes for your most complex scenarios. Data drives the model to optimize the outcomes. AI is the program logic to interpret machine learning results.

  • Broadest Set of ML Services

    With the most comprehensive ML and AI services, we can help you quickly build, train and deploy machine learning models at scale with pre-trained services and support for open-source frameworks.

  • Expert Certified resources 

    With our CXOS architectures, ML and AI initiatives can be deployed in weeks instead of months. And with ongoing support through our CXOS On-Demand Managed Services.

  • Lower Costs

    AWS provides secure, virtually unlimited access to data and power at scale. Its on-demand availability means you don’t need to purchase expensive, specialized technology that sits unused most of the time.

Data Analytics

A standard element of on-premise data centers, data warehouses have been used by business intelligence and analytics teams to uncover insights and provide reports by making sense of the company’s historical structured data. However, these data warehouses have not been able to keep up with the new data sources. They are rigid monolithic architectures that are difficult to scale and maintain. They are no longer cost-effective or sustainable.

New data sources, including streaming data, semi-structured data, text, and voice, all fall outside the highly structured transactional data box. However, they must be accessed and appropriately analyzed without affecting compute and performance levels. Cloud technology offers high performance, simple deployment, near-infinite scaling, and easy administration at a fraction of the cost of on-premises solutions. Eplexity’s Data Analytics modernization delivers benefits more suited to modern data types, today’s sophisticated analytics tools, and computing workloads.

Data Lakes

Data and data sources are rapidly growing both in volume and diversity, consider the proliferation of IoT devices, social media streams, and user data to name just a few. This massive amount of unstructured data also needs to be securely stored so it can be accessed and analyzed by any number of applications and people to uncover important business insights. AWS powered data lakes are centralized, secure, and cost-effective.

  • Load any amount of data in real time without needing to define a schema
  • Eliminate data silos by loading any data type into your data lake
  • Get to insights faster with a variety of machine learning tools
  • Enable data scientists, analysts, and developers to use their own analytics tools
  • Enjoy rigorous security and governance for all of your data stored in your data lake