Chordia is launching Compass™ - an interaction analysis engine built on a simple idea: the first step to improving customer conversations is understanding what actually happened in them.
That sounds obvious. But most of the tools designed for this job don't actually do it. They score. They sample. They reduce a complex human interaction to a number on a checklist. Compass takes a different approach.
Compass processes customer conversations - calls, chats, any transcribed interaction - and produces structured, evidence-based analysis. Not a score. Not a sentiment label. A complete account of what happened, grounded in specific moments from the transcript.
Every insight Compass generates traces back to evidence: the exact words, the timestamp, the context. Nothing is inferred without a basis. Nothing is asserted without proof.
The system detects over 300 behavioral signals across resolution, rapport, compliance, sales effectiveness, and more. Each signal carries a strength score indicating how strongly the behavior was present - not just whether it happened, but how much it mattered.
The hardest problem in conversation analysis isn't detecting what happened. It's determining whether what happened was good.
A customer who calls to cancel is different from a customer who calls with a quick question. Evaluating both agents the same way - same scorecard, same benchmarks - punishes the one who handled the harder call. Every QA manager knows this. Most tools ignore it.
Compass introduces Agent Lift, a patent-pending scoring method that measures how much an agent's behavior changed the likely outcome of a conversation, adjusted for difficulty. An agent who handles a tough call well and shifts the outcome in a positive direction gets credit for that. An agent who coasts through an easy call doesn't get inflated marks.
Agent Lift doesn't rank agents against each other. It measures each agent's impact on each conversation. The result is a performance signal that's fair, auditable, and useful for coaching - not punishment.
Compass evaluates human agents and AI agents using the same framework. As organizations deploy AI in customer-facing roles - chatbots, voice agents, agentic workflows - they need a consistent standard for understanding how those interactions go.
Most QA tools were built for human agents. They assume a supervisor is listening, a form is being filled out, a sample is being reviewed. That model doesn't scale to AI agents handling thousands of interactions per hour.
Compass doesn't care who's on the other end of the conversation. The same evidence-based analysis applies. Human, AI, or blended - every interaction gets the same treatment. One standard. One source of truth.
For decades, quality assurance in customer operations has relied on scorecards and call sampling. A supervisor listens to a handful of calls, checks boxes, assigns scores. Maybe 2-5% of interactions ever get reviewed.
The result is a system built on judgment rather than evidence. Scores vary by reviewer. Feedback is generic. Agents don't trust it. And the 95%+ of calls that never get reviewed? Nobody knows what happened in them.
Compass replaces that system with one built on understanding. Every conversation gets analyzed. Every insight is grounded in evidence. Every piece of coaching guidance is tied to something that actually happened - not a generic tip from a training manual.
The shift isn't from manual QA to automated QA. It's from judgment to truth.
Compass is available today. To see it in action or connect it to your conversation data, request a demo.
Chordia builds interaction intelligence for teams that manage customer conversations at scale. Learn more at chordia.ai.
