How platform teams ship AI agents to production with Tray and Amazon Bedrock—featuring architectures, frameworks, and real use cases.
AI is reshaping workflows across support, IT, finance, and compliance—but most teams stall before reaching production. This guide breaks down how to go from prototype to production, fast—using Tray and Amazon Bedrock.
Inside: a full delivery framework, real-world architectures, and practical use cases to help you build agents that actually work.
Move agents from prototype to production: Follow a step-by-step framework for design, build, deployment, and iteration. Covers everything from setting objectives to ongoing refinement and monitoring.
Cut build time with a flexible, low-code architecture: See how Tray and Amazon Bedrock remove common delivery roadblocks using prebuilt connectors, prompt tooling, and reusable workflows—without rewriting your stack.
Close the gaps that stall most AI projects: Address the real blockers, including governance blind spots, fragmented systems, security risks, and the overhead of custom dev work.
Apply a real production architecture—built around Slack: Get the exact components behind an AI support agent that classifies tickets, generates responses, and refines outputs using live feedback—built with Tray, Amazon Bedrock, and Vector Tables.