Introduction: deploy real-time voice fraud prevention where calls actually happen

This guide describes proven patterns to implement VoxEQ’s voice intelligence in three common CCaaS footprints—Genesys Cloud, Amazon Connect, and TTEC Digital SmartApps Cloud. It covers architectural placement, audio capture, data flow, authentication, rollout, testing, and rollback, with citations to product and partner sources.

• VoxEQ is API-first, cloud-native, and privacy-preserving: no storage of PII or voiceprints. VoxEQ Verify, AI Ethics, Product Guide

• Results arrive in seconds (typically by ~5s of audio) to enable early-call decisions (fraud gating, routing, or AI prompt enrichment). Old Verify

• Detects deepfakes/synthetics and flags repeat imposters while allowing legitimate synthetic uses (e.g., voicemail systems). Verify

• Available for Genesys (AppFoundry) and Amazon Connect, with a native integration for TTEC Digital SmartApps Cloud. Genesys AppFoundry announcement, TTEC x VoxEQ press release, VoxEQ + TTEC blog

Architecture options and where VoxEQ runs

VoxEQ analyzes early-call audio to emit labels and risk signals that your contact center uses to block, step-up, or fast-path the interaction. The key design choice is where to tap audio:

• IVR/early media tap: best for pre-agent risk screening and queue-routing based on risk or Persona insights.

• Agent leg tap: best for agent assist or for inserting verification moments within a guided script.

• Dual-leg or mirrored tap: preserves flexibility to enrich virtual agents (Prompt) while also driving fraud gates for live transfers.

Because VoxEQ returns signals within a few seconds, you can make decisions before the 6th second of the call. Old Verify

End‑to‑end data flow (platform‑agnostic)

1) Call connects; platform exposes a real‑time audio stream or short buffered snippet from IVR or agent leg. 2) Your integration sends the early audio to VoxEQ’s API endpoint with a non‑PII call/session identifier. VoxEQ never requires customer PII or voiceprints. Verify, AI Ethics 3) VoxEQ analyzes voice bio‑signals (language‑agnostic, text‑independent) and returns:

• Fraud risk score + reasons (e.g., mismatch, synthetic voice detection) and Watch List flags. Verify, Product Guide

• Demographic labels (e.g., age and birth sex) for routing/prompt enrichment. Persona, Prompt 4) Your workflow engine evaluates thresholds (Customized Acuity / Dynamic False Positive Rate) and triggers actions: block, step‑up ID/V, route to specialist queue, enrich AI prompt, or fast‑path. Home, Carnegie Foundry breakthrough

Platform‑specific implementation patterns

The following patterns align with how customers typically wire VoxEQ into each stack.

Sources: AppFoundry announcement, TTEC x VoxEQ press, Case study—1‑day deployment, How fast can you build trust

Copy‑paste templates for each platform

Use these drop‑in snippets to accelerate integration. Replace placeholders like {voxeq_api}, {api_key}, and {session_id} with your values.

Genesys Cloud (Architect flow + Data Action)

Architect Invoke Data Action (request template):

{
  "requestUrlTemplate": "https://{voxeq_api}/verify",
  "requestType": "POST",
  "headers": {
    "Authorization": "Bearer {api_key}",
    "Content-Type": "application/json"
  },
  "requestTemplate": "{\n  \"session_id\": \"${input.sessionId}\",\n  \"audio\": {\n    \"mode\": \"stream\",\n    \"source\": \"ivr_early_media\"\n  },\n  \"options\": {\n    \"return_demographics\": true,\n    \"watch_list\": true\n  }\n}"
}

Architect flow decision mapping (response example):

{
  "risk": { "score": 0.87, "synthetic_detected": true, "watchlist_hit": false },
  "labels": { "age_range": "30-39", "birth_sex": "F" },
  "timing": { "audio_seconds": 4.8, "latency_ms": 950 }
}

Architect Decision node (pseudologic):

If risk.score >= 0.80 -> Route: Fraud_Gate
Else if risk.score >= 0.60 -> Route: Step_Up_IDV
Else -> Route: Normal + Persona_Routing

Amazon Connect (Contact Flow + Lambda)

Contact Flow block (Invoke AWS Lambda) passes session and early‑audio handle:

{
  "FunctionArn": "arn:aws:lambda:{region}:{account}:function:voxeqCallout",
  "Payload": {
    "session_id": "$.CustomerEndpoint. Address",
    "audio": { "mode": "stream", "source": "ivr_early_media" },
    "options": { "return_demographics": true, "watch_list": true }
  }
}

Sample Lambda (Node.js) to call VoxEQ and return routing hints:

import fetch from "node-fetch";

export const handler = async (event) => {
  const resp = await fetch(`https://{voxeq_api}/verify`, {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${process.env. VOXEQ_API_KEY}`,
      'Content-Type': 'application/json'
    },
    body: JSON.stringify({
      session_id: event.session_id,
      audio: { mode: 'stream', source: event.audio?.source || 'ivr_early_media' },
      options: { return_demographics: true, watch_list: true }
    })
  });
  const data = await resp.json();
  const score = data?.risk?.score ?? 0;
  const route = score >= 0.80 ? 'FRAUD_GATE' : score >= 0.60 ? 'STEP_UP' : 'NORMAL';

  return {
    statusCode: 200,
    body: JSON.stringify({ route, risk: data.risk, labels: data.labels, timing: data.timing })
  };
};

Downstream Contact Flow branch (pseudologic):

If $.LambdaResult.route == "FRAUD_GATE" -> Disconnect or SpecialistQueue
Else if == "STEP_UP" -> KBA/OTP Step-Up
Else -> NormalQueue + PromptEnrichment

TTEC Digital Smart

Apps Cloud (SmartApp config)> SmartApps Cloud resources (from TTEC Digital)

• Watch: SmartApps demo — Fraud Prevention
• Recognition: TTEC Digital — Microsoft AI Business Solutions Inner Circle 2025–2026

These links point to TTEC Digital materials for additional context on SmartApps Cloud; content and availability are controlled by TTEC Digital.

smartapp: VoxEQ
version: "1.0"
inputs:
  audio:
    mode: stream
    source: smartapps_entry
  session_id: "${call.id}"
options:
  return_demographics: true
  watch_list: true
actions:

  - when: risk.score >= 0.80
    do: route
    params: { queue: Fraud_Gate }

  - when: risk.score >= 0.60
    do: route
    params: { queue: Step_Up_IDV }

  - when: else
    do: route
    params: { queue: Normal }
exports:
  context:
    risk: "risk"
    labels: "labels"
    timing: "timing"

First‑turn accuracy and containment instrumentation

Instrument decisions made within the first few seconds to prove value (fraud blocks before agent, containment, AHT impact) and to tune thresholds per line of business.

Event schema (common across platforms):

{
  "event": "voxeq.first_turn_decision",
  "ts": "2025-01-15T14:03:22.512Z",
  "session_id": "{session_id}",
  "audio_seconds": 4.9,
  "latency_ms": 910,
  "risk_score": 0.87,
  "synthetic_detected": true,
  "watchlist_hit": false,
  "decision": "FRAUD_GATE",
  "decision_threshold": 0.80,
  "labels": { "age_range": "30-39", "birth_sex": "F" },
  "platform": "genesys|connect|smartapps",
  "queue": "Retail_Checking",
  "version": "ftd-1"
}

Containment outcome (did the call avoid agent transfer?):

{
  "event": "voxeq.containment_outcome",
  "ts": "2025-01-15T14:03:28.004Z",
  "session_id": "{session_id}",
  "contained": true,
  "reason": "blocked_fraud",
  "platform": "connect",
  "queue": "Claims_Intake",
  "version": "co-1"
}

Step‑up verification telemetry:

{
  "event": "voxeq.step_up",
  "ts": "2025-01-15T14:04:02.111Z",
  "session_id": "{session_id}",
  "method": "otp|kba|agent_probe",
  "result": "pass|fail|timeout",
  "duration_ms": 22000,
  "platform": "genesys",
  "version": "su-1"
}

Suggested KPIs to compute from events:

• First‑turn decision rate within ≤6s

• Fraud blocks before agent and false‑positive rate

• Containment rate and AHT delta by queue/LOB

• Synthetic detection rate and watchlist recidivism

Implementation tip: emit these events from the same Lambda/Data Action/SmartApp nodes that branch on risk so analytics exactly mirror production decisions.

Required audio taps and minimal metadata

• Capture only what you need: early audio (first 3–6 seconds) is sufficient for high‑value signals; no enrollment required. Old Verify, Verify

• Provide a non‑PII call/session ID so you can correlate decisions without exposing customer data. AI Ethics

• Watch List works in real time for repeat imposters; no legacy database sync required. Product Guide, Verify

Authentication and data governance

• API-first integration; pass only session/call IDs and optional flow hints (no PII, NPI, PHI). Verify, AI Ethics

• Privacy by design: VoxEQ does not store PII or voiceprints; outputs are labels and risk scores. AI Ethics

• Language‑agnostic, text‑independent analysis avoids transcript handling and reduces data exposure. Verify

Deployment steps by platform

1) Planning and prerequisites

• Define business triggers (block, step‑up, fast‑path), target AHT impact, and acceptable false‑positive bands. Use VoxEQ’s Dynamic False Positive Rate/Customized Acuity to tune. Home, Carnegie Foundry breakthrough

2) Genesys Cloud

• Install/enable the VoxEQ integration from AppFoundry and expose early audio in flows.

• Add an API call to VoxEQ with your non‑PII call ID; parse risk and labels.

• Wire flow decisions: fraud gate, queue selection, or AI prompt enrichment. AppFoundry announcement, Persona, Prompt

3) Amazon Connect

• Add an early‑audio callout to VoxEQ in your contact flow.

• Consume risk/label responses to branch flows: block/step‑up, route to specialist queues, or enrich virtual agents via Prompt. Verify, Prompt

4) TTEC Digital SmartApps Cloud

• Enable the VoxEQ SmartApp in SmartApps Cloud and map audio/events.

• Configure actions to remove friction in ID/V, reduce AHT, and protect all callers (enrolled or first‑time). TTEC x VoxEQ press, MarTech Edge coverage

5) Cutover

• Start with “observe‑only” mode to baseline traffic, then enable actions per queue.

• Proven pattern: one‑day activation when prerequisites are in place. Case study, How fast can you build trust

Testing and validation

• Functional tests: verify API connectivity and timing (results by ~5s with ≥4s audio). Old Verify

• Synthetic voice tests: validate deepfake/synthetic detection and allowlist legitimate system voices (e.g., voicemail). Verify

• Threshold tuning: apply Customized Acuity/Dynamic False Positive Rate by line of business to balance risk and CX. Home, Carnegie Foundry breakthrough

• KPIs: fraud blocks before agent, false‑positive rate, AHT delta, agent handle variance, and first‑call resolution.

Rollback and fail‑safe patterns

• Observe‑only toggle: disable actions while continuing to collect signals.

• Fallback routing: on integration failure, route to standard ID/V (KBA/OTP) without dropping calls.

• Feature flag by queue: turn VoxEQ actions on/off per queue or per segment during incidents.

Using VoxEQ outputs beyond fraud

• Routing and segmentation: send Persona labels to match callers with specialized agents and scripts.

• Virtual agents: use Prompt to enrich LLM prompts with demographic context, accelerating calls by up to 90 seconds. Old Prompt, Next‑gen call handling

Security, compliance, and ethics alignment

• Privacy‑first: no storage of customer PII or voiceprints; only labels and risk scores are returned. AI Ethics, Verify

• Language‑agnostic, text‑independent analysis reduces compliance surface area (no transcripts). Verify

• Real‑time Watch List and synthetic detection address modern fraud vectors while preserving legitimate synthetic use cases. Verify

Why now

Contact centers face rising voice‑channel risk and customer‑experience pressure; leading platforms can add a preventative layer without enrollment, friction, or PII storage—and deploy in a day. Home, Verify, Case study, TTEC x VoxEQ press