--- title: "AWS Bedrock Integration" description: "Run inference against Amazon Bedrock foundation models from Anthropic, Amazon, Meta, Mistral, Cohere, and Stability AI through one connector, and discover which models your account can call." url: https://flowrunner.ai/integrations/aws-bedrock date_modified: 2026-08-07T17:20:23-07:00 --- # AWS Bedrock [AI](https://flowrunner.ai/integrations/category/ai-llms) Run inference against Amazon Bedrock foundation models from Anthropic, Amazon, Meta, Mistral, Cohere, and Stability AI through one connector, and discover which models your account can call. [Verified](https://flowrunner.ai/integrations/verified "What does verified mean?") · 5 actions · API key · available [AWS Bedrock website](https://aws.amazon.com/) · [Platform Documentation](https://aws.amazon.com/bedrock/) · Capability data verified 2026-07-14 1. New support case created in the queue 2. Agent sends the case text to Invoke Model for classification 3. Model returns the category, urgency, and a one-line summary 4. Agent routes low-urgency cases automatically by category 5. Agent assigns the case to the right team 6. Team channel gets the summary and category 7. High-urgency or ambiguous cases route to a lead before assignment ## What This Integration Enables Bedrock gives an agent access to a catalog of foundation models without leaving AWS. The connector invokes a model, streams or returns the completion, and lists the models your account can call, so inference stays inside the account, region, and IAM boundaries your security team already signed off on. For an AWS-native operation, that removes a common objection to putting a model in a production flow: the data never leaves the tenant. What makes it operational rather than experimental is the layer around the call. An orchestration layer routes the model's output into the next system and pulls a person in when the stakes warrant it, and FlowRunner is built for that layer. ### Without FlowRunner **Models outside AWS**: Inference runs on a separate vendor, outside existing governance **One model, hard-coded**: Switching foundation models means a new integration **Cases sorted by hand**: Support staff read and route every incoming case ### With FlowRunner **Inference inside AWS**: Model calls run under the same account and region as your data **Any Bedrock model**: Anthropic, Amazon, Meta, and more behind one connector **Cases pre-sorted**: The model categorizes and routes before anyone opens the queue ## Use Case Scenarios ### Support Case Classification Every new support case needs a category, an urgency read, and a team. The agent sends the case text to a Bedrock model and gets back a structured classification. Low-urgency cases route automatically by category. The model handles the sorting that used to consume the first hour of every support shift, and the queue is triaged before anyone opens it. ### Internal Knowledge Answers Employees ask the same policy and process questions repeatedly. The agent retrieves the relevant internal documents, passes them to a Bedrock model with the question, and returns a grounded answer inside AWS so no internal content leaves the account. Answers that the model is confident about return directly; anything touching a sensitive policy is routed to the owning team instead of answered automatically. ### Document Summarization at Scale Long reports pile up faster than anyone reads them. The agent sends each report to a Bedrock model for a structured summary with key figures and risks, then files the summary alongside the original. Reviewers read a short brief with the source one click away. When the model flags a figure it is unsure about, the summary marks it for a person rather than presenting it as fact. ## Human-in-Loop Highlight A model running inside your AWS account is still a model, and its output is still an input to a decision, not the decision itself. When a Bedrock call produces a classification, an answer, or a summary that drives a real action, FlowRunner routes it through a [human-in-the-loop](https://flowrunner.ai/concepts/human-in-the-loop) step: the agent pauses, assembles the model's output and the context behind it, and sends it to the right person via Slack or email. They decide. The model handles the volume; a person owns the judgment calls. Agent processes routinely Detects exception requiring judgment Clear match Continues automatically Ambiguous Routes to human via Slack Human decides Agent resumes with decision ## Agent Capabilities 5 actions ### Inference 3 - **Converse** Sends messages to a Bedrock foundation model through the unified Converse API, which works identically across Anthropic Claude, Amazon Nova/Titan, Meta Llama, Mistral, Cohere, and other chat models. - **Invoke Model** Invokes a Bedrock model directly with a raw, model-specific request body and returns the parsed model-specific response. - **Generate Image** Generates an image from a text prompt using an image model such as amazon. titan-image-generator-v2:0 or a Stability AI model, then saves the decoded PNG to FlowRunner file storage and returns a downloadable URL. ### Models 2 - **List Foundation Models** Lists the Amazon Bedrock foundation models available in the configured region, with optional filtering by provider name or output modality. - **Get Foundation Model** Retrieves the full details of a single Amazon Bedrock foundation model by its model ID, including provider, supported modalities, streaming support, inference types, and lifecycle status. ## Frequently Asked Questions ### What can FlowRunner do with AWS Bedrock? FlowRunner agents can run Converse, Invoke Model, and Generate Image in AWS Bedrock, plus 2 more actions. ### Does connecting AWS Bedrock to FlowRunner require OAuth? No. AWS Bedrock connects to FlowRunner with an API key, no OAuth flow required. ### Can AWS Bedrock trigger a FlowRunner workflow automatically? AWS Bedrock doesn't currently expose triggers in FlowRunner. It connects as an action step inside workflows started by another trigger. **Work at AWS Bedrock?** This integration exposes AWS Bedrock to AI agents on every FlowRunner plan, including through MCP, at no cost to you. [See what FlowRunner offers integration partners](https://flowrunner.ai/integrations/partners), including how to keep this page current. --- Markdown version of https://flowrunner.ai/integrations/aws-bedrock. Site index: https://flowrunner.ai/llms.txt