Data Discovery Agent

Challenge: Efficient Data Discovery & Validation at Scale:

As organizations manage growing volumes of data, the process of discovering and validating datasets becomes slow and inefficient. Fragmented metadata, inconsistent quality indicators, and lack of contextual understanding in existing tools lead to delays in analytics and reduced trust in data. This increases reliance on engineering teams for manual validation, hindering timely decision-making and data-driven insights.

Our Solution: AI-Driven Data Discovery Agent on AWS:

The AI-Driven Data Discovery Agent on AWS is a cloud-native solution that streamlines data discovery and validation. Built on Amazon EKS, it leverages AI and semantic search to provide natural-language search, intelligent recommendations, and data profiling. Seamlessly integrating with metadata stores and lineage services, it enables business users to quickly locate, assess, and validate datasets without deep technical expertise, improving collaboration, accelerating insights, and enhancing data trust across the organization.

Key Features & Capabilities:

• AI-powered search understands user intent and returns relevant datasets using contextual interpretation, reducing search time.

• Generates statistical summaries of datasets, such as volume, freshness, completeness, and null distributions, providing critical quality indicators.

• Provides secure, governed previews to ensure datasets meet user requirements before use in analytics or model development.

• Suggests related datasets, frequently used assets, and high-quality data sources to improve discovery across teams and projects.

• Coordinates communication between multiple specialized agents, maintaining context and aggregating results for a unified discovery experience.

Ideal Users & Organizations:

The AI-Driven Data Discovery Agent is ideal for organizations with large, complex data estates, particularly in industries like finance, healthcare, technology, and retail. It benefits business analysts, data scientists, and IT teams by providing quick access to validated datasets without relying on engineering. This solution supports data democratization, governance, and faster analytics, while fostering cross-team collaboration and reducing data silos.