Run RAG Without Sending Data to a Public AI
Build a private RAG pipeline over internal documents using AWS Bedrock Knowledge Base and Jinba, all inside your own VPC with no data leaving your environment.
Build a private RAG pipeline over internal documents using AWS Bedrock Knowledge Base and Jinba, all inside your own VPC with no data leaving your environment.
Japanese insurers' ops teams manually send claim-status updates over LINE. Jinba automates the send, logs every API response, and monitors quota so customers hear first.
Route regulated content through low, medium, and high-risk paths in Jinba Flow using the Grok tool for classification, with every model call logged automatically.
OCR gives you text, not structure. Jinba's OPENAI_INVOKE turns unstructured docs into JSON inside a workflow, then routes parsed fields to Snowflake or Sheets.
The real question for regulated teams isn't which tool indexes the most connectors. It's whether the tool can take a compliant action on what it finds, inside a boundary the business controls.
CFOs kill AI budgets because vendors hand them feature lists, not numbers. This three-part ROI framework quantifies productivity loss, compliance risk, and token cost waste in terms finance teams recognize.
LLM oversharing, cloud-only deployment, and stochastic outputs trip compliance audits. Three tools evaluated on the criteria that keep IT directors and compliance officers out of trouble.
Generic AI governance platforms monitor models. Banks need governance at the workflow execution layer, where LLMs touch KYC documents and underwriting decisions, and only one platform on this list governs there.
A 5-section printable checklist for security and compliance teams evaluating AI workflow platform RBAC: agent identity scoping, execution-level audit logs, SSO/AD/SCIM integration, and on-prem deployment.