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fazeZEROApplication Atlas

Demo listing. This page uses illustrative seed metadata to demonstrate the Atlas. Claims shown here are not verified product facts.

Polaract

Marketing & Growth

Demo

Classifies social customer-care utterances into fine-grained dialogue acts while correctly scoping negation cues so “not working” is never treated like “working.”

Design onlyfazeZERO VerifiedProprietary

Last verified 15 Sept 2026 · Updated 23 Sept 2026 · Metadata v4

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Configuration + implementation engagement

Problem

Brand Twitter / X (and similar public social) customer-care teams whose agent assist and bot routing break on informal negated complaints.

Outcome

A design-complete foundation in the active pipeline — engineering scaffold planned to complete this month.

Who uses it

  • Operations Analyst
  • Solution Architect

Key capabilities

Capabilities are defined during customer configuration.

Typical workflow

Primary operating flow

Trigger: An operator starts the primary use case

  1. Task

    Stage 1: Capture inputs

    Operator

  2. AI-assisted

    Stage 2: Assist with draft

    System

  3. Human checkpoint

    Stage 3: Human approval

    Approver

Task Automated AI-assisted Human checkpoint Decision

About this foundation

Negation-first dialogue-act intelligence for social care. Generic intent classifiers ignore cue scope on tweets; Polaract commercialises IBM Research’s finding that heuristic negation scope (−1/+2 windows, POS, emotion-word) plus NOT_ feature transforms measurably lift multi-label dialogue-act F-scores on informal care text — where CRF models trained on formal English underperform.

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