Building a Real-Time Agent Assist Transcript Parser with TypeScript and Genesys Cloud WebSockets

What You Will Build

You will build a TypeScript service that connects to the Genesys Cloud real-time conversation stream, parses transcript segments into structured payloads, applies speaker turn detection and PII redaction, triggers keyword highlights via the Agent Assist annotation API, and synchronizes parsed results to external CRM plugins via webhooks. This tutorial uses the Genesys Cloud REST API and WebSocket streaming endpoints with TypeScript and Node.js.

Prerequisites

• OAuth Client Credentials flow with scopes: conversation:read, agentassist:read, agentassist:write, analytics:read
• Genesys Cloud REST API v2
• Node.js 18+ with TypeScript 5+
• External dependencies: npm install ws axios dotenv uuid zod
• Environment variables: GENESYS_BASE_URL, GENESYS_CLIENT_ID, GENESYS_CLIENT_SECRET, CRM_WEBHOOK_URL

Authentication Setup

Genesys Cloud requires a Bearer token for both WebSocket subscription and REST annotation calls. The Client Credentials flow is appropriate for server-side parsing services. You must cache the token and handle expiration to prevent 401 interruptions during long-running WebSocket sessions.

import axios from 'axios';
import dotenv from 'dotenv';

dotenv.config();

const GENESYS_BASE_URL = process.env.GENESYS_BASE_URL || 'https://api.mypurecloud.com';
const CLIENT_ID = process.env.GENESYS_CLIENT_ID!;
const CLIENT_SECRET = process.env.GENESYS_CLIENT_SECRET!;

interface AuthToken {
  access_token: string;
  expires_in: number;
  token_type: string;
}

class AuthManager {
  private token: string | null = null;
  private expiresAt: number = 0;

  async getToken(): Promise<string> {
    if (this.token && Date.now() < this.expiresAt) {
      return this.token;
    }

    const response = await axios.post<AuthToken>(
      `${GENESYS_BASE_URL}/oauth/token`,
      new URLSearchParams({
        grant_type: 'client_credentials',
        client_id: CLIENT_ID,
        client_secret: CLIENT_SECRET,
        scope: 'conversation:read agentassist:read agentassist:write analytics:read'
      }),
      { headers: { 'Content-Type': 'application/x-www-form-urlencoded' } }
    );

    this.token = response.data.access_token;
    // Subtract 60 seconds for safe refresh margin
    this.expiresAt = Date.now() + (response.data.expires_in - 60) * 1000;
    return this.token;
  }
}

Implementation

Step 1: WebSocket Connection and Stream Subscription

Genesys Cloud delivers real-time transcript data through a persistent WebSocket connection. You must send a subscription message immediately after connection to receive analytics:conversationDetails events. The service must handle reconnection and buffer pressure to respect maximum streaming limits.

import WebSocket from 'ws';
import { v4 as uuidv4 } from 'uuid';

interface StreamEvent {
  type: string;
  data: {
    conversationId: string;
    transcript: TranscriptSegment[];
  };
}

interface TranscriptSegment {
  from: string;
  to: string;
  text: string;
  startTime: number;
  endTime: number;
}

const MAX_BUFFER_LIMIT = 500;

class TranscriptStream {
  private ws: WebSocket | null = null;
  private buffer: TranscriptSegment[] = [];
  private auth: AuthManager;
  private onSegment: (segment: TranscriptSegment) => void;

  constructor(auth: AuthManager, onSegment: (segment: TranscriptSegment) => void) {
    this.auth = auth;
    this.onSegment = onSegment;
  }

  async connect(): Promise<void> {
    const token = await this.auth.getToken();
    const wsUrl = `${GENESYS_BASE_URL.replace('https://', 'wss://')}/api/v2/analytics/conversations/details/stream`;
    
    this.ws = new WebSocket(wsUrl, {
      headers: { Authorization: `Bearer ${token}` }
    });

    this.ws.on('open', () => {
      const subscription = {
        type: 'subscribe',
        channels: ['analytics:conversationDetails'],
        options: { conversationIds: [] }
      };
      this.ws?.send(JSON.stringify(subscription));
    });

    this.ws.on('message', (data: WebSocket.Data) => {
      const event: StreamEvent = JSON.parse(data.toString());
      if (event.type === 'analytics:conversationDetails' && event.data.transcript) {
        this.processStream(event.data.transcript);
      }
    });

    this.ws.on('close', () => {
      console.warn('WebSocket disconnected. Reconnecting in 5s...');
      setTimeout(() => this.connect(), 5000);
    });

    this.ws.on('error', (err) => {
      console.error('WebSocket error:', err.message);
    });
  }

  private processStream(segments: TranscriptSegment[]): void {
    for (const segment of segments) {
      if (this.buffer.length >= MAX_BUFFER_LIMIT) {
        console.error('Maximum streaming buffer limit reached. Dropping segment to prevent backpressure failure.');
        continue;
      }
      this.buffer.push(segment);
      this.onSegment(segment);
    }
  }
}

Step 2: Parse Payload Construction and Schema Validation

You must construct parse payloads that reference the transcript ID, organize segments into a matrix structure, and define annotation directives. Validation against the assist engine constraints prevents malformed payloads from triggering parsing failures.

import { z } from 'zod';

interface SegmentMatrix {
  [key: string]: TranscriptSegment[];
}

interface AnnotationDirective {
  type: 'keyword' | 'decision' | 'note';
  targetPhrase: string;
  confidence: number;
  metadata: Record<string, unknown>;
}

interface ParsePayload {
  transcriptId: string;
  segmentMatrix: SegmentMatrix;
  annotationDirectives: AnnotationDirective[];
  parsedAt: string;
}

const ParsePayloadSchema = z.object({
  transcriptId: z.string().uuid(),
  segmentMatrix: z.record(z.string(), z.array(z.object({
    from: z.string(),
    to: z.string(),
    text: z.string(),
    startTime: z.number(),
    endTime: z.number()
  }))),
  annotationDirectives: z.array(z.object({
    type: z.enum(['keyword', 'decision', 'note']),
    targetPhrase: z.string().min(1),
    confidence: z.number().min(0).max(1),
    metadata: z.record(z.unknown())
  })),
  parsedAt: z.string().datetime()
});

function validateParsePayload(payload: ParsePayload): boolean {
  const result = ParsePayloadSchema.safeParse(payload);
  if (!result.success) {
    console.error('Parse schema validation failed:', result.error.errors);
    return false;
  }
  return true;
}

Step 3: Speaker Turn Detection and PII Redaction Pipeline

The assist engine requires clean text for phrase extraction. You must detect speaker turns to separate agent and customer utterances, then run a PII redaction pipeline to prevent data exposure before triggering annotations.

interface RedactionPipeline {
  detectSpeakerTurn(segments: TranscriptSegment[]): { currentSpeaker: string; turnCount: number };
  redactPII(text: string): string;
}

const PII_PATTERNS = [
  { type: 'email', regex: /\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b/g },
  { type: 'phone', regex: /\b\d{3}[-.]?\d{3}[-.]?\d{4}\b/g },
  { type: 'ssn', regex: /\b\d{3}-\d{2}-\d{4}\b/g }
];

class RedactionPipeline implements RedactionPipeline {
  detectSpeakerTurn(segments: TranscriptSegment[]): { currentSpeaker: string; turnCount: number } {
    let currentSpeaker = segments[0]?.from || 'unknown';
    let turnCount = 1;
    for (let i = 1; i < segments.length; i++) {
      if (segments[i].from !== segments[i - 1].from) {
        currentSpeaker = segments[i].from;
        turnCount++;
      }
    }
    return { currentSpeaker, turnCount };
  }

  redactPII(text: string): string {
    let sanitized = text;
    for (const pattern of PII_PATTERNS) {
      sanitized = sanitized.replace(pattern.regex, `[REDACTED_${pattern.type.toUpperCase()}]`);
    }
    return sanitized;
  }
}

Step 4: Phrase Extraction and Keyword Highlight Triggers

You must extract phrases atomically from the sanitized segments and push keyword highlights to the Agent Assist API. The REST call requires retry logic for 429 rate limits and format verification to ensure the assist engine accepts the directive.

import axios, { AxiosError } from 'axios';

interface KeywordTrigger {
  phrase: string;
  startTime: number;
  endTime: number;
}

class KeywordHighlighter {
  private auth: AuthManager;
  private redaction: RedactionPipeline;

  constructor(auth: AuthManager) {
    this.auth = auth;
    this.redaction = new RedactionPipeline();
  }

  async extractAndHighlight(conversationId: string, segment: TranscriptSegment): Promise<void> {
    const sanitizedText = this.redaction.redactPII(segment.text);
    const phrases = this.extractPhrases(sanitizedText);

    for (const phrase of phrases) {
      const directive: AnnotationDirective = {
        type: 'keyword',
        targetPhrase: phrase.phrase,
        confidence: 0.95,
        metadata: { source: 'transcript-parser', timestamp: new Date().toISOString() }
      };

      const payload: ParsePayload = {
        transcriptId: conversationId,
        segmentMatrix: { [conversationId]: [segment] },
        annotationDirectives: [directive],
        parsedAt: new Date().toISOString()
      };

      if (!validateParsePayload(payload)) {
        console.warn('Skipping invalid payload for conversation:', conversationId);
        continue;
      }

      await this.postAnnotation(conversationId, directive);
    }
  }

  private extractPhrases(text: string): KeywordTrigger[] {
    const triggers: KeywordTrigger[] = [];
    const keywords = ['escalation', 'refund', 'cancel', 'complaint'];
    const lowerText = text.toLowerCase();
    
    for (const keyword of keywords) {
      const index = lowerText.indexOf(keyword);
      if (index !== -1) {
        triggers.push({ phrase: keyword, startTime: 0, endTime: keyword.length });
      }
    }
    return triggers;
  }

  private async postAnnotation(conversationId: string, directive: AnnotationDirective): Promise<void> {
    const token = await this.auth.getToken();
    const url = `${GENESYS_BASE_URL}/api/v2/agent-assist/annotations`;
    
    const requestBody = {
      conversationId,
      type: directive.type,
      payload: {
        target: directive.targetPhrase,
        confidence: directive.confidence,
        metadata: directive.metadata
      }
    };

    try {
      await this.retryWithBackoff(() =>
        axios.post(url, requestBody, {
          headers: {
            Authorization: `Bearer ${token}`,
            'Content-Type': 'application/json',
            'Accept': 'application/json'
          }
        })
      );
    } catch (err) {
      const axiosErr = err as AxiosError;
      if (axiosErr.response?.status === 403) {
        console.error('403 Forbidden: Missing agentassist:write scope or insufficient permissions.');
      } else if (axiosErr.response?.status === 422) {
        console.error('422 Unprocessable Entity: Annotation payload format verification failed.');
      } else {
        console.error('Annotation POST failed:', axiosErr.message);
      }
    }
  }

  private async retryWithBackoff(fn: () => Promise<void>, retries = 3): Promise<void> {
    for (let i = 0; i < retries; i++) {
      try {
        await fn();
        return;
      } catch (err) {
        const axiosErr = err as AxiosError;
        if (axiosErr.response?.status === 429 && i < retries - 1) {
          const delay = Math.pow(2, i) * 1000;
          console.log(`Rate limited (429). Retrying in ${delay}ms...`);
          await new Promise(resolve => setTimeout(resolve, delay));
        } else {
          throw err;
        }
      }
    }
  }
}

Step 5: CRM Webhook Sync, Metrics, and Audit Logging

You must synchronize parsed events with external CRM plugins, track parsing latency and extraction success rates, and generate structured audit logs for assist governance. The webhook call operates asynchronously to prevent blocking the main parsing thread.

import fs from 'fs';

interface ParseMetrics {
  totalSegments: number;
  successfulExtractions: number;
  failedExtractions: number;
  averageLatencyMs: number;
  lastUpdated: string;
}

class ParserGovernance {
  private metrics: ParseMetrics = {
    totalSegments: 0,
    successfulExtractions: 0,
    failedExtractions: 0,
    averageLatencyMs: 0,
    lastUpdated: new Date().toISOString()
  };
  private auditLogPath: string = 'agent-assist-audit.log';

  async syncToCRM(conversationId: string, payload: ParsePayload): Promise<void> {
    const webhookUrl = process.env.CRM_WEBHOOK_URL;
    if (!webhookUrl) {
      console.warn('CRM_WEBHOOK_URL not configured. Skipping sync.');
      return;
    }

    const startTime = Date.now();
    try {
      await axios.post(webhookUrl, {
        event: 'transcript_parsed',
        conversationId,
        payload,
        syncedAt: new Date().toISOString()
      }, { timeout: 5000 });
      
      const latency = Date.now() - startTime;
      this.updateMetrics(latency, true);
      this.writeAuditLog('CRM_SYNC_SUCCESS', conversationId, latency);
    } catch (err) {
      const axiosErr = err as AxiosError;
      this.updateMetrics(0, false);
      this.writeAuditLog('CRM_SYNC_FAILED', conversationId, 0, axiosErr.message);
    }
  }

  private updateMetrics(latency: number, success: boolean): void {
    this.metrics.totalSegments++;
    if (success) {
      this.metrics.successfulExtractions++;
      this.metrics.averageLatencyMs = 
        (this.metrics.averageLatencyMs * (this.metrics.totalSegments - 1) + latency) / this.metrics.totalSegments;
    } else {
      this.metrics.failedExtractions++;
    }
    this.metrics.lastUpdated = new Date().toISOString();
  }

  private writeAuditLog(action: string, conversationId: string, latencyMs: number, error?: string): void {
    const logEntry = JSON.stringify({
      timestamp: new Date().toISOString(),
      action,
      conversationId,
      latencyMs,
      error,
      metrics: this.metrics
    }) + '\n';
    fs.appendFileSync(this.auditLogPath, logEntry);
  }

  getMetrics(): ParseMetrics {
    return { ...this.metrics };
  }
}

Complete Working Example

The following module integrates all components into a single runnable parser service. You must set the required environment variables before execution.

import { AuthManager } from './auth'; // Assumes previous auth code is in this file or imported
import { TranscriptStream } from './stream'; // Assumes previous stream code
import { KeywordHighlighter } from './highlighter'; // Assumes previous highlighter code
import { ParserGovernance } from './governance'; // Assumes previous governance code
import { ParsePayload, validateParsePayload } from './validation'; // Assumes previous validation code

async function main(): Promise<void> {
  const auth = new AuthManager();
  const governance = new ParserGovernance();
  const highlighter = new KeywordHighlighter(auth);

  const segmentHandler = async (segment: TranscriptSegment) => {
    const conversationId = segment.from.includes('agent') ? 'conv-001' : 'conv-002';
    
    try {
      await highlighter.extractAndHighlight(conversationId, segment);
      
      const payload: ParsePayload = {
        transcriptId: conversationId,
        segmentMatrix: { [conversationId]: [segment] },
        annotationDirectives: [],
        parsedAt: new Date().toISOString()
      };

      if (validateParsePayload(payload)) {
        await governance.syncToCRM(conversationId, payload);
      }
    } catch (err) {
      console.error('Parse iteration failed:', err);
    }
  };

  const stream = new TranscriptStream(auth, segmentHandler);
  console.log('Initializing transcript parser...');
  await stream.connect();

  // Graceful shutdown handler
  process.on('SIGINT', () => {
    console.log('\nShutting down parser. Final metrics:', governance.getMetrics());
    process.exit(0);
  });
}

main().catch(console.error);

Common Errors & Debugging

Error: 401 Unauthorized on WebSocket Connection

• Cause: The OAuth token expired before the WebSocket handshake completed, or the client credentials lack the conversation:read scope.
• Fix: Ensure the AuthManager refreshes the token before every connection attempt. Verify the OAuth client in the Genesys Admin console has the conversation:read and analytics:read scopes assigned.
• Code Fix: The AuthManager implementation already subtracts 60 seconds from the expiration window to force a safe refresh. If 401 persists, log the exact timestamp and compare it against the token expires_in value.

Error: 422 Unprocessable Entity on Annotation POST

• Cause: The annotation payload contains invalid field types, or the targetPhrase exceeds the assist engine character limit.
• Fix: Use the Zod schema validation before sending. Ensure confidence is a float between 0 and 1. Verify type matches supported annotation types.
• Code Fix: The validateParsePayload function catches schema violations. Add length checks to extractPhrases if your assist engine enforces a strict maximum phrase length.

Error: WebSocket Buffer Overflow and 429 Cascades

• Cause: The parsing pipeline processes segments slower than the Genesys stream delivers them, causing the internal buffer to exceed MAX_BUFFER_LIMIT or triggering rate limits on downstream CRM calls.
• Fix: Implement backpressure handling by dropping non-critical segments or batching CRM webhooks. Increase the retry delay for 429 responses.
• Code Fix: The processStream method checks this.buffer.length >= MAX_BUFFER_LIMIT and drops segments gracefully. The retryWithBackoff method applies exponential backoff specifically for 429 responses.

Error: PII Redaction Pipeline Misses Variants

• Cause: Regular expressions do not cover all regional phone formats or email obfuscation patterns.
• Fix: Extend the PII_PATTERNS array with additional regex variants. Consider using a dedicated PII detection library for production scaling.
• Code Fix: Replace the static regex array with a configurable pipeline that accepts external pattern definitions.

Official References

• Genesys Cloud Real-Time Conversation Details WebSocket API
• Genesys Cloud Agent Assist Annotations API
• Genesys Cloud OAuth 2.0 Client Credentials Flow
• TypeScript WebSocket Client Library (ws)
• Zod Schema Validation Library