Policy assistance
Retrieve approved procedures and cite the underlying knowledge used to form an answer.
Solution pattern · Banking
How AI agents can support banking workflows
Design assistants for policy navigation, operations, and internal service workflows while keeping deployment, identity, tool scope, and confirmation under institutional control.
- AI agents for banking
- banking AI agent
- AI in banking workflows
Where it can help
AI agents for banking: practical use cases
These are implementation patterns, not claims about unnamed customers. The exact scope depends on your systems, permissions, controls, and acceptance criteria.
Operations support
Delegate narrowly defined tasks to specialists with separate tool access.
Controlled action
Forward identity to the system of record and pause high-impact calls for confirmation.
Reference architecture
Secure AI agents: control at every boundary
SyntheticBrew handles reasoning and orchestration. Your application remains responsible for authentication, domain authorization, and the data or actions exposed through each tool.
- Internal banking application
- Self-hosted SyntheticBrew runtime
- Scoped specialists, knowledge, audit, and confirmation
- Institutional APIs that enforce RBAC and tenant boundaries
Production controls included
- Per-agent tool and MCP server scoping.
- Forwarded JWT, organization, user, and tenant context.
- Confirmation gates before consequential actions.
- Structured events for progress, errors, and completion.
- Self-hosted or Cloud deployment with your choice of LLM.
Other solution patterns
More AI agent use cases
Choose how you want to ship.
Evaluate the workflow in Cloud, run the open-source engine on your infrastructure, or book your personal sales call for a delivered implementation.