Taxbit Assist: A grounded, role-aware AI agent on Amazon Bedrock AgentCore
AWS Machine Learning Blog · 人工智能
Taxbit is a digital-asset tax and accounting compliance platform. Founded in 2018, Taxbit helps enterprises such as exchanges, payment services, and brokers calculate gains and losses, collect tax documentation, and file information returns at scale. Now, a cited, permission-aware AI assistant helps compliance teams find answers right inside the product dashboard. But the knowledge needed to use that dashboard well was scattered across the public website, API documentation, and help-center articles, and a meaningful share was never written down at all. When a customer asked “what does this form status mean?”, they either went digging or filed a support ticket. Today more than 55 percent of users who ask Assist a question return to ask another within 24 hours, according to Taxbit’s internal production analytics. In this post, we share how we built Taxbit Assist , the AI assistant now embedded in the Taxbit dashboard, on Amazon Bedrock AgentCore , a platform to build, connect, and optimize agents at scale, with any framework or model. We cover the architecture, the retrieval work that made answers trustworthy enough to ship to regulated customers, how we handle safety and data residency, and how we continuously measure answer quality on live production traffic. What the assistant had to get right A generic chatbot was not an option in this domain. Four constraints shaped what we built: Grounded and cited – Our users make filing decisions. Every answer had to trace back to a source the user could open and read, and when the assistant didn’t know something, it had to say so. Role and organization awareness – The assistant shouldn’t walk a Support User through an admin-only workflow and send them to a page that they can’t open. No tax advice – Explaining how Taxbit computes cost basis (the accounting method used to compute a gain or loss) is product documentation. Telling a user which method to elect is tax advice. The line between the two is narrow. Regional data reside