A personalized learning assistant on AWS rarely fails loudly. It fails by being helpful to the wrong student. Five failure families that decide whether an AI tutor built on Amazon Bedrock is safe to put in front of a class: LTI identity, retrieval isolation, guardrail limits, the cost shape of an academic term, and being able to prove what the assistant saw.
S3 holds the documents, Iceberg holds the rows, and everything works right up until a number disagrees with its source PDF. Combining structured and unstructured data on AWS is an identity problem, not a storage one. Here are the five failure families that cause it, why each stays invisible until it isn't, and the ingestion order that avoids most of them.
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.
Connecting Salesforce to Amazon Bedrock Knowledge Bases takes an afternoon. Making sure the assistant does not read people records they were never allowed to see takes longer. A practical walkthrough of the connector, the permission model it quietly drops, and the two architectures that actually hold up.