Generative AI Begins With Data Strategy

In the current technology landscape, products like ChatGPT, Bard, and similar generative AI (Gen AI) solutions have captured the global imagination, promising a future where machines learn, adapt, and create on their own. However, the magic of AI doesn't begin with the algorithms or models—it starts much earlier. Just as a house cannot be built without first laying the foundation, AI cannot function effectively without the bedrock of a solid data strategy.

As an AWS Premier Consulting Partner with both the Data and Analytics and Machine Learning Competencies, ClearScale can provide the data architecture and data engineering services that are at the root of every successful GenAI project.

And with the ClearScale GenAI AppLink™, you’ll be able to effortlessly integrate transformative Large Language Models (LLMs) into your existing AWS landscape to harness the limitless potential of AI for your business.

“ClearScale recognized the importance of AWS’ Machine Learning paradigms to SeligoAI’s value proposition and their ability to generate probability-based intelligence. Complex AI algorithms also continuously modify the Working Dataset and continually refine the predictive model which refreshes the probability analyses. Essential to this set of core calculations is AWS’ ML platform.”

- Gregory Jordan, SeligoAI

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Our Data Architecture for Generative AI Services

  • Migrate Data

    Get your data into AWS so that you can begin to leverage it for your AI projects.

  • Design and Build Data Lakes

    Set up secure and scalable data lakes quickly to store your structured and unstructured data.

  • Explore Data

    Perform initial analyses and create visualizations to better understand your data.

  • Unify Data

    Consolidate your data across your data lakes and data warehouses to set the stage for data scientists to pursue more advanced use cases.

Our Data Engineering for Generative AI Services

  • Automate Data Processing

    Ensure data quality through efficient processing, labeling, and organizing, then plan ahead for deeper analyses

  • Analyze in Real Time

    Develop live analytics workloads that can keep up with big data volumes and generate insights continuously

  • ETL Data into Data Stores

    Extract, transform, and load into your data lakes and data warehouses according to your specific needs

  • Integrate Data Analytics

    Deliver advanced data visualization and analytics capabilities directly to end users through your applications.

Ensure Data Readiness for Your Generative AI Projects

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Unified Data Accessibility

Integrate your relational data into a single repository to facilitate seamless access for data analysts, data scientists, and engineers to build AI algorithms.

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Accelerated Data Processing

Enhance your data warehouse's efficiency, ensuring swift SQL queries, comprehensive reporting, and advanced analytics required by data scientists building advanced AI models.

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Optimized Data Reliability

Manage and categorize data based on your specific needs and use cases, guaranteeing your data’s consistency, accuracy, and readiness for your generative AI projects.