Prevent unsafe or incorrect financial or compliance-related outputs
In regulated domains, incorrect or speculative outputs create legal or financial exposure. Tests exercise these failure modes so they can be fixed before deployment.
What's at stake
- Financial outputs (quotes, statements, projections) can create binding commitments
- Compliance statements may be relied upon for regulatory filings or audits
- Incorrect outputs in regulated domains can trigger enforcement actions
- Speculative or invented financial data can mislead investors or customers
- Enterprise customers in regulated industries require documented output verification
How to solve this
Agents operating in financial or regulated domains face unique risks. Their outputs aren't just information—they're potential commitments, disclosures, or representations that carry legal weight.
The challenge is that LLMs don't distinguish between confident accuracy and confident fabrication. A speculative financial projection looks the same as a verified calculation. An invented compliance statement reads like a documented one.
The solution is to validate every regulated output before it leaves your system and to test systematically for the scenarios that produce unsafe outputs.
How Superagent prevents this
Superagent provides guardrails for AI agents—small language models purpose-trained to detect and prevent failures in real time. These models sit at the boundary of your agent and inspect inputs, outputs, and tool calls before they execute.
For regulated outputs, Superagent's Verify model checks financial and compliance content against your verified data sources. Financial figures are validated against your accounting systems. Compliance claims are checked against your certification status. Outputs that can't be verified are blocked or flagged.
Superagent's Adversarial Tests exercise the scenarios most likely to produce unsafe regulated outputs:
- Prompts that request financial projections or guarantees
- Questions about compliance status for certifications you don't hold
- Scenarios that combine valid and invalid financial data
- Edge cases in regulated terminology and disclosure requirements
Tests identify which prompts and contexts trigger unsafe outputs. Results feed directly into your remediation process—you know exactly what to fix before deployment.