Interpretable Intelligence: Why You Can Trust ACIAS
Human emotion isn’t binary. It’s layered, complex, and often ambiguous. No NLP system - not even a human - can decode every nuance perfectly. And unlike most tools, ACIAS doesn’t pretend to. Instead, it does something smarter:- It scores what’s clear.
- It flags what’s fuzzy.
What ACIAS Does Well (with High Confidence)
| Function | Confidence | Why It Works |
|---|---|---|
| Emotion scoring (Bliss, Ease, Kindness, etc.) | 90%+ | Based on direct language cues + consistent emotional scales |
| Pain/Plus Point tagging | 85–95% | Clear matching of language to themes + intensity scale |
| Journey stage assignment | 80–90% | Anchored to specific stage language ("checkout", "support", etc.) |
| Persona matching | 85–95% | Based on emotional signals and trigger phrases, scoped by domain |
| Churn/Compliance risk detection | 80–90% | Strong at surfacing emotional withdrawal, dissatisfaction, or distrust |
| Flagging emotional contradictions | 100% by design | Flags highlight inconsistencies, masking, or sarcasm - without mutating core scores |
What ACIAS Does Differently
Instead of forcing an answer, ACIAS surfaces flags where ambiguity or misalignment might exist:| Case | Example | ACIAS Response |
|---|---|---|
| Sarcasm or passive aggression | “Perfect, not.” / “Classic.” | flag: Sarcasm suspected – language/tone mismatch |
| Polite language masking frustration | “Thanks anyway.” | flag: Politeness masking churn – customer may be quietly unhappy |
| Contradictory scores | High Bliss + Stage Friction | flag: Loyalty cushioning friction – investigate flagged stages |
| Category conflict | “Fast delivery, but damaged again.” | flag: Conflicted Plus Point removed: Delivery |