Introduction
Large enterprises handle an immense volume of customer calls each month—ranging from routine inquiries to mission-critical support. For one Fortune 500 leader in the financial services sector, traditional contact center operations were struggling to keep up with escalating call volumes, rising costs, and multilingual customer expectations.
In less than four months, Wiserep helped them transform their customer experience by deploying AI-powered voice automation at scale. Here's how the journey unfolded.
Project Goals
Objectives:
Deployment Timeline
Assessment and Alignment (Weeks 1-2)
- • Stakeholder workshops to map key pain points and business priorities
- • Review of call data: 18,000+ inbound calls per month, 60% routine tasks
- • Compliance and data privacy gap analysis (GDPR, industry regs)
Technical Integration (Weeks 3-6)
- • SIP and PBX integration for seamless call routing
- • Bi-directional data sync with legacy CRM
- • Secure SSO and RBAC onboarding for IT and ops teams
AI Training & Pilot (Weeks 7-10)
- • Uploading and annotating historical call transcripts (~1M records)
- • Custom intent models and language packs for target scripts
- • Progressive rollout: AI handled 15% of total call volume in first two weeks
Full Production Launch (Weeks 11-16)
- • Expand AI coverage to all basic inquiries (account status, document requests, claims)
- • Activate failover routes for complex or escalated calls to human agents
- • Live dashboards and weekly analytics reviews with client team
Technical Challenges and Solutions
Complex Legacy Systems
Designed middleware adapters to bridge on-premise PBX and Wiserep's cloud-native AI platform.
Multilingual Consistency
Deployed advanced, culturally-aware language models to ensure fluency and correct intent across regional dialects.
High Security Requirements
Full encryption for all voice, transcript, and integration data (AES-256, TLS 1.3), plus granular access controls and automated audit logs.
Customer Experience
Crafted custom voice personas and tested over 250 sample flows to match the brand's tone and empathy standards.
Measurable Business Outcomes
Call Automation Rate
Of monthly inbound calls fully handled by AI, freeing up agents for high-value scenarios.
Cost Savings
Reduction in per-call servicing costs, mainly via lower staffing and overtime needs.
Wait Time
Median wait time for all automated interactions (previously 2–5+ minutes in peak hours).
CSAT Scores
Satisfaction rate maintained on post-call surveys for automated and agent-assisted queries.
Compliance & Reporting
Automated GDPR-compliant consent, detailed call logs, and robust audit trails for all interactions.
Lessons Learned
Change Management Is Critical
Success required active collaboration with frontline agents for AI training and feedback.
Integration Drives Results
Deep, real-time integration with telephony and CRM ensured no data silos and a seamless customer journey.
Iterative AI Optimization
Regular, data-driven tuning of intents and conversation flows delivered ongoing gains in automation and CX.
Conclusion
AI automation at enterprise scale is entirely achievable—with the right technology, strategy, and partnership. By leveraging Wiserep, this Fortune 500 client rapidly delivered measurable improvements in efficiency, compliance, and customer satisfaction, handling millions of calls per month with ease.