AI Data Readiness Scan

Duration: 4 weeks
Price (excl. VAT): 32.700 EUR
Number of persons: n/a

About the AI Data Readiness Scan

“Is our data valuable and capable of driving AI applications?”

That’s the first question that should come to mind before developing an AI-driven application. Data is the lifeline of AI. Its value is only unlocked when the data is quality assured and AI ready.

Our AI Data Readiness Scan assesses the quality, structure, and readiness of your data. Over the course of 4 weeks, we’ll provide a clear roadmap on how to increase its value and transform it into a strategic asset that drives AI innovation in your organization.

Our scan is tailored to your unique business context, and will be the driver for impactful AI initiatives and real-time decision making.

What to expect

Week 1: Kickoff and data identification

  • We align with business and technical stakeholders on AI use cases.
  • We identify and catalog relevant data sets for these use cases.

Week 2: Data quality assessment

  • We assess the quality and format of the identified data sets.
  • We determine the cleanliness, completeness, and consistency of the data.

Week 3: Pilot testing and preliminary analysis

  • We run pilot exercises to test the usability of the data in specific AI models.
  • We evaluate the initial performance of the AI models using current data.

Week 4: Data usability synthesis and recommendations

  • We synthesize the findings from the previous weeks into a comprehensive report.
  • We provide recommendations for improving data usability for specific AI use cases in your organization.

Your data is ready for AI. Now what?

You can count on Xylos to be your partner in the next stages of your AI journey: creating your own AI application that adds value to your business. From speeding up routine tasks to improving decision-making, supporting creativity or boosting customer service: the possibilities are endless.

Take a look at our products and use cases:

The target audience

The AI Data Readiness Scan provides added value to organizations that rely on accurate and compliant data, with a focus on operational efficiency, the use of predictive analytics, and process improvement through AI technologies.

For example:

  • In healthcare, AI can greatly improve diagnostics, treatment, personalization, and operational efficiency.
  • In finance and banking, AI can improve the accuracy of risk assessment, fraud detection, and regulatory compliance.
  • For the energy and utilities industry, AI can help manage and predict energy consumption, optimize grid operations, and enhance sustainability initiatives through predictive analytics based on reliable data.
  • Manufacturing companies can use AI applications to optimize production lines, predict maintenance, and improve supply chain management, which requires the integration and analysis of vast amounts of operational data.
  • The transportation and logistics industry can benefit from AI to optimize logistics operations, enhance route planning, and improve real-time decision making to reduce costs and increase delivery efficiency.

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