From raw data to decision-ready data, without a brittle stack.
AWS environments often collect disconnected data lakes, warehouses, ETL jobs and duplicated business logic. That raises cost, slows delivery and leaves AI teams without reliable, governed data.
- Disconnected lakes, warehouses and ETL jobs
- Business logic duplicated across pipelines
- No shared access rules or lineage
- AI teams waiting for trusted data
Built in your AWS account.
S3 and Apache Iceberg as an open storage layer for batch, streaming and API data.
- Amazon S3 and Apache Iceberg
- AWS Glue and Spark processing
- Amazon MSK and CDC ingestion
Lake Formation, IAM and KMS enforce access, lineage and audit from day one.
- Lake Formation access policies
- Data quality, catalog and lineage
- IAM, KMS and network security
Athena and Redshift for your data warehouse workloads, and the same governed data for your RAG pipelines and AI agents.
- Athena and Redshift analytics
- Data products for AI agents
- CI/CD, monitoring and runbooks
From kickoff to your first use case in production on AWS.
Events per day processed on AWS architectures.
Records engineered in Apache Iceberg.
Results in production
Questions we hear
Why Apache Iceberg?+
It is an open table format. Your data stays in S3, readable by Athena, Redshift, Spark and other engines, so you can change tools without moving data.
Can you modernize our existing data lake or warehouse?+
Yes. We use AI to convert legacy SQL and ETL code, engineers review every result, and reconciliation checks prove the outputs match before each cut-over.
Do we need the whole lakehouse before AI?+
No. We build the part the first use case needs and extend it with each new one.
Where does it run, and who owns what?+
In your own cloud account or on your servers, under your access controls. The work we build for your platform is yours: pipelines, data models, infrastructure code and documentation. Accelerators we reuse across clients stay ours, with a permanent licence for you to run and change them in your platform. Our own agents, such as Intelligent DataOps, will run on a subscription. If you cancel, your platform keeps running without them.
What happens after the Sprint?+
You can run it yourself, extend it with a Build, or have us operate it with Managed. Agents from the Sprint continue on a subscription.
Build the AWS data foundation your AI agents can trust.
Tell us what you run on AWS today and your first use case.