Continuously monitor customer conversations for missed disclosures, risky language, and compliance gaps—without relying on sampling or manual review.
Compliance Monitoring is a core capability of Chordia’s Customer Conversations Operating System, which treats compliance as an outcome of how conversations actually unfold—continuously, consistently, and at scale.
Compliance issues rarely announce themselves. They show up in small misses—an incomplete disclosure, an improvised promise, a missed verification step—spread across thousands of interactions.
Traditional monitoring relies on sampling and after-the-fact audits, which means risk is often found late and coverage is incomplete.
The highest-risk moments tend to occur in edge cases: escalations, emotional calls, exceptions to normal workflows, and situations where agents improvise under pressure.
Instead of reviewing a small sample of interactions, compliance can be monitored consistently across every conversation—using your requirements and evidence from what was said and when.
Define what must happen in a compliant interaction—required disclosures, verification steps, prohibited language, and any rules that depend on call context.
Compliance expectations should be explicit and shared across teams so monitoring is consistent and defensible—not dependent on who reviewed the call.
A compliance flag is only useful when it can be traced back to the conversation itself.
Each finding should reference the exact moment it occurred (or should have occurred), with supporting quotes and timestamps. This makes reviews faster, reduces ambiguity, and helps teams agree on what happened.
Compliance monitoring matters when it prevents repeat issues and reduces exposure.
The output should surface patterns, highlight recurring misses, and make it easy to prioritize coaching and remediation—without increasing manual review burden.
Compliance is checked through periodic reviews of a small sample of calls.
Coverage is limited, issues are discovered late, and findings can vary by reviewer—making it hard to prove consistency or identify systemic gaps.
• Sample-based coverage
• After-the-fact detection
• Reviewer-dependent judgment
Every interaction can be checked against the same requirements—not just a small sample.
Monitoring is evidence-backed, with findings tied to specific conversation moments, so teams can validate quickly and act confidently.
• Consistent rules at scale
• Earlier risk detection
• Evidence in context
Chordia surfaces missed disclosures and risky moments across every interaction, so teams can reduce exposure without expanding manual audits.
If you want to see how compliance monitoring fits into your operation—and how evidence-backed findings improve reviews and coaching—we can walk through it using your requirements and real examples.
