From answers to outcomes: agents with AWS Bedrock AgentCore in Financial Service
GenAI has moved past “answering well” and started to truly move the needle. The real jump happens when an assistant understands customer context, decides the next action, and operates internal systems with least-privilege access and full traceability. In this article, we’ll explore how AWS Bedrock AgentCore—currently in preview—lays the foundation for taking agents to production in regulated environments.
In that sense, AWS Bedrock AgentCore shows up as the foundation for taking agents to production in regulated environments: agent identity, real-work tooling, observability, and a runtime that doesn’t lock you into a single framework or model.
Where things get stuck today
Recommendations that don’t turn into actions. Many assistants suggest, but don’t execute: they don’t raise limits, open cases, or kick off onboarding.
Sensitive access. Letting an agent act “on behalf of” a user without overexposing credentials is hard.
Low decision transparency. Without a step-by-step trail, it’s tough to debug, learn, and pass audits.
Homemade tools. Automating internal web apps, running trustworthy calculations, or exposing standard tools often ends up fragile.
What AgentCore changes
Agents with their own identity. They act with least-privilege and short-lived credentials; they can represent the system or a user with explicit consent.
End-to-end observability. Visualizing trajectories (what it decided, when, and why) enables continuous improvement and auditability.
Tooling for real-world tasks.
- Browser tool: interacts with internal or external web apps securely and without juggling multiple browser sessions.
- Code interpreter: runs logic in a sandbox (validations, simulations, reproducible reporting).
- Gateway/Runtime: exposes your APIs and tools including support for standards such as the Model Context Protocol (MCP).
- Stack-agnostic: Orchestrate with the framework you prefer and choose the foundation model by cost/latency/quality—on or off Bedrock.
The reference architecture on AWS
- Agent core: AgentCore (Identity, Observability, Memory, Gateway, Runtime, Tools).
- Models and orchestration: Foundation models in Amazon Bedrock (and external) with optional use of Bedrock Agents for opinionated orchestration flows.
- Knowledge: Knowledge Bases for grounding with policies, manuals, and rate tables; optional OpenSearch for hybrid retrieval (text + vectors).
- Operating channels: Amazon Connect and Contact Lens to enable agent assist and surface agent decisions in the service desktop.
- Data and governance: S3/Lake Formation/Glue/Athena for content and logs; IAM/CloudTrail/CloudWatch/PrivateLink/KMS for access, audit, observability, and end-to-end encryption.
Three scenes that show value
- Digital onboarding and KYC that doesn’t jam
The agent guides onboarding, flags missing items, checks consistency, consults watchlists, and updates systems. If it needs to jump into an internal console, it uses the browser tool; if it needs calculations, it runs them in the code interpreter.
Result: fewer drop-offs and shorter onboarding times, with clear traceability for compliance.
- A relationship manager and agent desktop that actually closes
During the interaction, the agent pulls the right policy, proposes the next best action (e.g., restructure a balance), simulates scenarios in the interpreter, and—when appropriate—executes adjustments via API using temporary credentials. The supervisor sees the decision trace and scores the recommendation.
Impact: lower average handle time, higher first-contact resolution, and standardized compliance.
- Explainable risk, fraud, and compliance
When an alert fires, the agent combines signals (repositories, data lake), replays steps in an internal app via the browser tool, and generates a reproducible report with the code interpreter. Everything is logged for audit.
Effect: less rework and faster audit responses.
Governance
- Least-privilege access and short expiration for agent credentials (including “on-behalf-of”).
- Isolated interpreter executions and controlled navigation in the browser tool.
- Complete traceability with events and metadata for every decision.
- Private, encrypted traffic within the perimeter (VPC endpoints/PrivateLink, KMS), plus IAM controls and logging with CloudTrail.
Anti-patterns that kill ROI—and how to avoid them
An assistant that “opines” but doesn’t operate. Define up front what the agent can do and when a human steps in.
Fuzzy permissions. Separate identities (agent/user/service), use tight scopes and short-lived credentials.
Operational blindness. Without trajectories and decision-quality metrics, there’s no improvement.
Duct-taped tooling. Standardize the browser, interpreter, and gateway to avoid technical debt and speed up hardening.
Our approach
At Switch, we deliver agents ready to operate in regulated environments:
- Immediate-impact use cases: onboarding/KYC, agent assist that closes, fraud/compliance, collections.
- Secure-by-design architectures: AgentCore + Bedrock (Knowledge Bases, Guardrails) integrated with your APIs and channels.
- Evidence from day one: referenced responses, visible decision traces, and business metrics.
The differentiator isn’t about explaining better anymore—it’s about resolving with control. With AWS Bedrock AgentCore and the Bedrock stack, you move from a friendly chatbot to a financial agent that understands context, honors policies, and executes actions.
If you’d like, get in touch and we’ll spin up a demo in your environment to see how we can help.
Disclaimer: Amazon Bedrock AgentCore is currently in preview, and features may evolve prior to general availability.