For enterprises running AI workloads on AWS, the infrastructure question is largely solved. Amazon S3, Amazon Redshift, AWS Glue, Amazon Athena. The data is moving, the pipelines are running, and the models are ready to be put to work.
The question that remains is harder: does the AI actually understand what the data means?
Knowing a column exists is not the same as knowing which definition is canonical, who owns it, whether it can be used for a given regulatory purpose, or whether the pipeline that feeds it has been validated. Without that context, AI agents answer confidently and wrongly. Pilots succeed; production stalls.
Atlan is the context layer for the AWS data and AI platform. Available on AWS Marketplace, Atlan connects natively to Amazon Redshift, Amazon S3, AWS Glue, Amazon Athena, Amazon QuickSight, and Amazon SageMaker — capturing lineage automatically, enriching metadata with AI-generated context, and enforcing governance policies that travel with the data wherever it goes.
As Subhasis Bhattacharya, Global Technical Lead for Data and Analytics at AWS, puts it: “With Atlan on AWS Marketplace, our customers can quickly add layers of trust and governance to their data stack without high upfront costs or long setup times.”
The result is an AWS data estate that agents can reason on — not just query. Enterprises including Nasdaq, Contentful, Mercury Insurance, New York Life, and Plaid already rely on Atlan and AWS together to do exactly that.
A leading US mortgage lender: governance as the foundation for AI
A leading US mortgage lender runs one of the most data-intensive operations in financial services. Loan origination, servicing, risk modeling, regulatory reporting, and customer programs all depend on the same underlying data assets — many of which live across an AWS-centric cloud platform that is progressively replacing legacy on-premises systems.
The problem was not a lack of data. It was a lack of context. Analysts and product teams struggled to find the right assets, understand lineage, and trust the metrics behind customer and risk decisions. With significant regulatory requirements around lending and model risk management, “we think this is the right table” was not an acceptable standard.
The team deployed Atlan as the central metadata hub across their AWS data estate, connecting Amazon S3, Amazon Redshift, AWS Glue, Amazon Athena, and a range of adjacent systems including Salesforce and business intelligence tools. AI Steward workflows generate and standardize descriptions at scale, flag missing glossary terms referenced in dashboards and models, and enrich domain-specific assets using industry-standard terminology, accelerating coverage across the organization.
The result is a governed context layer that sits above the AWS data plane: every asset described, every lineage path traceable, and every AI agent operating on sensitive data equipped with the context it needs to return a result that compliance teams can audit. Governance, in this case, does not slow the AI program down. It is what makes the AI program possible.
A major media and entertainment company: making a multi-platform estate AI-ready
A major US media and entertainment company manages data across news, sports, and streaming at significant scale. Its architecture is anchored on AWS, with Amazon Redshift as a core analytics platform alongside a broader data stack spanning multiple engines and processing layers depending on the workload. The result is a powerful but fragmented estate: rich with data, difficult for analysts and business users to navigate quickly or trust completely.
The governance challenge is compounded by the nature of the business. Content rights, regional restrictions, and user consent requirements mean agents operating on audience, advertising, or content data cannot simply retrieve whatever they find. Policies have to travel with the data.
Atlan is deployed as the metadata control plane across the full estate, connecting AWS-hosted assets with the rest of the data stack to give teams a consistent, governed view of data regardless of where it lives. Lineage runs from source through transformation to the BI layer, so analysts can understand not just what a dataset contains but how it was built and whether it can be used for a given purpose.
The team is also building a capability that allows business users to query data in plain language and receive curated datasets rather than ad-hoc SQL, grounded in the governed metadata layer Atlan maintains across the AWS estate. It is a practical demonstration of what AI-ready data looks like in production: not just data that has been cleaned and organized, but data an agent can understand, trust, and retrieve correctly.
The pattern
Across industries and architectures, the same pattern holds. Enterprises shipping production AI on AWS are not doing it by improving the model. They are doing it by improving the context the model has access to. That means lineage auditors can follow, descriptions that reflect the business rather than just the schema, and policies that prevent agents from retrieving data they should not touch.
The organizations that figure this out first will not just have better AI. They will have a compounding advantage: a context layer that grows richer with every query, every correction, every new asset catalogued. That is what Atlan and AWS are building together.
Ready to make your AWS data estate AI-ready?
See Atlan on AWS →FAQs about Atlan and AWS
What AWS services does Atlan connect to natively?
Atlan connects natively to Amazon Redshift, Amazon S3, AWS Glue, Amazon Athena, Amazon QuickSight, and Amazon SageMaker — capturing lineage automatically and enriching metadata with AI-generated context across all of them.
How does Atlan help enterprises deploy AI agents on AWS?
Atlan acts as the context layer for the AWS data estate, ensuring AI agents have access to governed, lineage-traced data with descriptions that reflect the business rather than just the schema — and policies that prevent agents from retrieving data they should not access.
Is Atlan available on AWS Marketplace?
Yes. Atlan is available on AWS Marketplace, allowing customers to add governance and context to their data stack without high upfront costs or long setup times.
