A confident answer with a citation from a matter the reader was walled off from. Nothing crashed, nothing alerted. Building legal document intelligence on AWS with Textract, Bedrock and OpenSearch is the easy half; the hard half is tenant isolation, verified deletion, S3 Object Lock holds, what leaves the account, and an audit trail that names the actual user.
Most as-planned vs as-built analysis compares the baseline to the last P6 update and calls the result an as-built. It isn't one. This is how to build the data layer underneath a delay analysis: versioned XER ingestion, activity identity across renumbering, a first-appearance table that proves when every actual date entered the record, calendar-safe float, and record linking that proposes candidates instead of asserting cause.
Semantic search finds the most persuasive document, not the earliest one. Here is how to architect an AI construction claims and dispute intelligence platform on AWS so retrieval respects the contractual clock, schedule data stays out of the vector index, every answer resolves to a page, and privileged material never shares a retrieval path with project records.
A practical architecture for a secure AI medical assistant on AWS, organised by the boundary the data crosses: the input box, your own invocation logs, cross-Region inference routing, the retrieval index, and clinical accuracy. Includes real commands, the failure modes that stay invisible until an audit, and the trade-offs worth knowing before you build.
A working engineer's guide to HIPAA compliance on AWS, organised by the gap between the control you configured and the obligation you actually carry. Covers BAA account scope, the eligible services list as a contract boundary, KMS key policy versus the encryption checkbox, what "six years" really applies to, backup and restore scope, and the subprocessor chain nobody inventories.