In high-stakes, regulated environments, quality assurance can’t be a sampling exercise. Yet most contact centres still review a tiny fraction of customer interactions, relying on time-pressed auditors and manual workflows. The result? Blind spots, inconsistent scoring, slow feedback and, ultimately, avoidable risk.
Quality Sentinel from cAI UK changes that equation. It applies AI to audit 100% of calls, emails and webchats in near real time, giving leaders a complete view of performance, compliance and customer experience, without expanding headcount or diluting standards.
This article is the second in our series exploring cAI’s solutions from a real user’s perspective. Today we focus on Quality Sentinel: what it is, the problems it solves, how it works, and what it actually feels like to use day to day. To ground this in reality, we weave in insights from Amy Taylor, QA & Training Manager at coeo UK, who is actively using the platform.
Traditional QA struggles to keep pace with modern customer engagement. Multiple channels, rising volumes, evolving regulations and varied agent skill levels mean manual auditing simply can’t scale. Quality Sentinel is a modern answer: an AI-driven quality monitoring platform built for collections and other regulated contact centre industries, applying consistent, objective scoring at scale and surfacing actionable feedback instantly.
Where a human auditor might sample a handful of interactions, Quality Sentinel reviews every interaction, automatically assessing compliance, tone, sentiment, disclosure, KPI adherence and more. That means fewer blind spots, faster coaching cycles and stronger assurance.
As Amy explains:
“On average an auditor completes around 15 call audits per day, whereas QA Sentinel can audit 100% of calls. The big uplift in calls being monitored means we’re getting a truer reflection of call quality across the contact centre, allowing us to tailor our coaching and training for those who need it most.”
In other words, Quality Sentinel shifts QA from a sample to a complete view. Leaders get a reliable baseline, and organisations can prioritise the people and moments that matter most.
What users see in practice:
“QA Sentinel used regularly has many benefits. It reduces the pressure on a QA team, as call auditing volumes are managed effectively by AI. This frees up time for coaching and feedback and helps highlight who’s doing particularly well and who may need additional support.”
So instead of chasing quotas, QA teams can invest their energy where it counts, developing people and lifting overall performance.
Quality Sentinel brings structure and momentum to QA by combining full-population coverage with near real-time scoring and consistent, criteria-led assessments. Instead of sporadic sampling and delayed feedback, teams get a clear, always-on picture of performance: what happened, why it mattered, and what to do next; so coaching becomes targeted, timely and scalable.
Complete coverage: Every call, email and webchat is analysed. This enables population-level QA, not just sample-level QA.
Real-time feedback: Interactions are scored in near real time, enabling instant coaching opportunities and proactive remediation.
Consistent, scalable scoring: The platform applies your QA criteria objectively, removing bias and eliminating repetitive manual work, so QA teams can focus on coaching, remediation and strategic improvement.
Quality Sentinel evaluates compliance, tone, sentiment, questioning technique, disclosures and KPI adherence, and can also suggest follow-up questions agents might ask to better understand a customer’s circumstances.
Amy notes that:
“QA Sentinel has been built to score a call just as a human would. It picks up on language used, tone, and looks for information we would expect an agent to give the customer. It can pick up on the type of questioning asked and then comment on what else could have been asked to understand a customer’s circumstances better.”
The takeaway: you get human-like judgement at machine scale; consistent, explainable assessments that point agents to concrete next steps.
Because every interaction is analysed, leaders see aggregate trends and individual performance in one place. Amy recommends daily use: near-real-time scoring offers “a good insight into an agent’s QA performance,” while team leaders can drill into individual scorecards to tailor coaching.
When the system flags issues, the feedback is clear and practical. coeo UK runs an internal QA framework in parallel, so surprises are rare, but the AI provides a much truer picture of where to focus and shares helpful, specific tips on how to improve.
Amy notes:
“Having an internal QA Team that scores calls using the same framework means any issues aren’t usually a surprise - however, QA Sentinel allows us to see a much truer picture of where there needs to be a focus.”
This alignment keeps expectations clear while the AI highlights precisely where additional support will make the biggest impact.
She continues:
“The feedback from the AI is very clear and offers helpful tips on how an agent can improve a certain aspect of a call.”
In practice, agents don’t just get a score: they get targeted, actionable guidance they can apply on the very next interaction.
One of the stand-out strengths is how simple it is to set up and adapt:
You collaborate on a scorecard aligned to your standards: regulatory criteria, brand tone, disclosures, vulnerability triggers and KPI expectations.
Quality Sentinel connects to existing contact-centre platforms. At coeo UK, scorecards are mapped to different call queues and tailored to how specific journeys should be handled. Updates are easy as regulations or internal policies evolve.
Agents see clear, readable scorecards; managers get background reporting that reveals QA performance across the operation, supporting continuous improvement.
As Amy describes the setup:
“Very simple. Scorecards can be built and matched to different call queues, then tailored to how a business expects calls to be handled. This can be monitored and amended easily over time in line with regulatory changes or business updates.”
That flexibility means the system stays in lockstep with your policies, processes and evolving regulatory requirements.
And on visibility:
“Individual scorecards are visible to an agent and are very clear to read and understand. Background reporting for management provides additional information around QA performance as a whole, making it a great tool to improve quality across the contact centre.”
The result is transparency for agents and control for managers, closing the loop between data, coaching and operational decisions.
Quality Sentinel isn’t static, it’s a living system driven by your policy updates, scorecard refinements and new data. In day-to-day use:
Amy highlights the momentum effect:
“We can see an average score per agent, which quickly highlights who’s excelling and who needs support. QA Sentinel can surface those needs much faster than manual sampling.”
With faster signal and clearer trends, teams can act earlier, preventing small issues from becoming systemic problems.
Let’s summarise the standout benefits businesses gain from deploying Quality Sentinel:
Quality Sentinel’s first impression is unmistakable: it delivers population-wide auditing with the kind of immediacy and precision that changes how teams manage quality. What stands out isn’t just the volume it can cover, but how quickly it translates analysis into clear, practical guidance for agents; turning QA into a genuinely live, performance-shaping capability.
Amy’s first reaction:
“The volume of calls it can monitor in such a short space of time is like nothing I have ever seen before. It can audit all calls almost in real time, much faster than any human can do it.”
This speed unlocks genuinely real-time quality management, turning QA from a retrospective check into a proactive lever.
She also points to accuracy:
“With the right prompts built into the scorecard it’s also very accurate, and the suggestions it gives an agent are very clear.”
That clarity builds trust: agents understand what “good” looks like, and leaders can evidence improvement with confidence.
Contact centre QA has long been constrained by limited coverage, subjective scoring and slow feedback loops. In regulated markets, where every word matters, those constraints translate directly into risk, cost and missed opportunities to improve.
Quality Sentinel provides a credible, modern alternative:
From coeo UK’s experience, the shift is immediate: greater coverage, clearer feedback, more focused coaching and a stronger, data-driven handle on quality across channels. Or, in Amy’s words, it gives a “truer reflection of the call quality across the contact centre,” freeing the QA team to coach and enabling leaders to act faster where it counts most.
If your organisation needs to reduce regulatory risk, improve agent performance and raise customer satisfaction, without adding headcount, Quality Sentinel is a smart place to start.
This article is part of our cAI UK spotlight series, exploring each solution from the user’s point of view. If you missed it, read our first post on Virtual Agent, and stay tuned for our final article, which brings Virtual Agent, Quality Sentinel and Customer Profiler together into one integrated, customer-centred AI toolkit.