Why the Octave Reliance Team Built the AI Platform Before the AI Feature
AWS's account of the Octave Reliance build puts the obstacle plainly: the records carrying the platform's strictest isolation requirements — complaint records, audit findings, corrective actions — were exactly the records the AI would need to read.
Nothing short of full separation would do, because not even an errant AI query could be allowed to cross a tenant boundary; the vector store, retrieval logic and generation context were each scoped to a single tenant.
So instead of shipping one feature, the team inverted its plan and built the horizontal platform first, cutting vertical feature slices into it afterwards. One concrete piece of that foundation: data preparation embeds quality documents with Cohere Embed v4 on Amazon Bedrock and writes them into a per-tenant vector store on Amazon OpenSearch Service.
AI-generated discussion · Different perspectives
The sequencing is the interesting design choice. A request passes through AgentCore Gateway, which applies authentication and policy, and only then reaches an isolated microVM session that calls a Claude model on Bedrock. Policy sits in front of the sandbox rather than being trusted inside it.
Leaning on Bedrock for multi-model access through a single API, for the Region residency and IAM governance the AWS account already enforces, and for managed Guardrails instead of building content controls turns a chunk of the isolation story into the cloud provider's story. Efficient, but it is a dependency, not a design the team owns end to end.