Helping Clip Adopt AI Agents for Customer Support: From Sampling to 100% Coverage

At InfiniteWatch, our core mission is to help companies like Clip adopt AI agents for customer support: safely, measurably, and at scale. Adopting AI agents is not just about switching on automation; it requires knowing exactly what happens in every customer conversation, so you can trust an AI agent to handle it. That is where our work with Clip began. As one of Latin America's fastest-growing payments companies, Clip was scaling faster than manual quality review could keep up with, and most of its customer interactions went unexamined.

At scale, most contact centers sample. QA reviews 1-2% of interactions across calls, WhatsApp threads, emails, and chat logs, flags what it happens to catch, and the rest goes unexamined. For a high-growth fintech like Clip, that blind spot compounds: undetected complaints become churn, unreviewed messages become compliance exposure, and unscored behaviour keeps repeating. The problem is not that teams don't care; it's that manual review cannot scale with volume, and it cannot give you the confidence to hand conversations to an AI agent.

The Challenge: Flying Blind at Scale

Clip handled 150,000 customer interactions per month across phone calls, WhatsApp, email, and live chat, spanning support, collections, onboarding, sales, and retention. QA coverage sat at just 1-2% of total interactions. Emerging issues took two to four weeks to surface. Scorecard updates took months and could not be tested against historical data before going live. Leadership had no unified view; managers worked from different datasets; agents got feedback on a fraction of their interactions. Without full visibility, Clip had no reliable baseline to decide where AI agents could safely take over.

The Solution: AI Voice Listener as the Foundation for AI Agent Adoption

InfiniteWatch deployed its AI Voice Listener across every channel Clip uses (phone calls, WhatsApp, email, and live chat), analysing 100% of interactions from day one. Every conversation is transcribed, scored against configurable scorecards, and surfaced in a shared dashboard accessible to leadership, managers, and agents. Crucially, the same scorecards apply to both human and AI-handled conversations, so as Clip introduces AI agents it can measure them against its people on identical quality and compliance criteria. This is the foundation of AI agent adoption: you can only trust an AI agent with a customer once you can prove, conversation by conversation, that it performs.

How It Works

• Full interaction coverage: every inbound and outbound phone call, WhatsApp conversation, email thread, and live chat session is automatically transcribed and analysed, with no sampling, no exclusions, no gaps between channels or business areas
• Automated scoring: each interaction is scored against customisable scorecards for quality, compliance, tone, and topic handling; scores are available within minutes of call completion
• Theme clustering: the system automatically groups interactions by customer issue, product area, and conversation outcome, surfacing the highest-volume themes and emerging patterns in near real time, pinpointing exactly which use cases are ready for an AI agent
• Scorecard back-testing: new scorecard versions can be tested against months of historical interactions before going live, removing the risk of deploying a scoring model that has not been validated
• Human-vs-AI benchmarking: because human and AI agents are scored on the same criteria, Clip can see where an AI agent already matches or beats human handling, and expand automation only where the data supports it
• Coaching workflows: managers see each agent's score distribution, trend lines, and specific calls flagged for coaching; agents have direct access to their own performance data between sessions
• Leadership dashboard: a single view across all business areas showing top customer themes, team performance benchmarks, quality trends, and the highest-value opportunities to introduce AI agents

Why This Matters for AI Agent Adoption

For Clip, 100% coverage was never the end goal; it was the prerequisite for confidently adopting AI agents. With every conversation scored, Clip can identify the exact intents and journeys where an AI agent is ready to take over, deploy it, and then watch it against the same benchmarks its human team is held to. When an AI agent underperforms on a scorecard, the gap is visible immediately; when it outperforms, Clip can expand it with evidence rather than guesswork. That feedback loop is how AI agent adoption becomes safe, gradual, and measurable, and it is exactly the outcome InfiniteWatch exists to deliver.

Key Results

Within six months, Clip's QA team shifted from manual review to coaching and structural improvements. Leadership could see every business area from a single dashboard, updated in near real time. For the first time, AI agents and human agents appeared side by side on the same metrics, showing where automation already matched or exceeded human handling and where people still performed better, giving Clip a clear, evidence-backed roadmap for scaling AI agents across customer support.

The ROI Picture

The 16x ROI at three months reflects both direct and indirect value: QA hours redirected to coaching, faster issue detection that prevents churn, compliance gaps caught before they escalate, scorecard iterations that took months now running in days, and, most importantly, a validated path to adopting AI agents where they demonstrably perform. Payback was reached in under two months.