Call volume, resolution rates, and outcomes in one dashboard, so every conversation turns into a decision.
In one view
Every call, measured
volume, outcomes, and conversion
What it does
Real-time view of volume, handle time, and outcomes.
Measure resolution and conversion by call type, not just totals.
Share performance insights across the business.
The basics
AI call analytics turn raw call activity into a reporting layer you can act on, measuring every inbound and outbound call by intent and outcome. Every call is captured and categorized, so you can see call volume, resolution and booking rates, lead conversion, peak hours, and sentiment trends in one place. Instead of digging through phone logs, decision-makers get live dashboards and exportable reports that show exactly how the phones, and the agent, are performing.
In short
Where it fits
Voice analytics for call centers has existed for twenty years, and for most of them it meant sampling a few percent of calls and scoring them against a checklist. Call center voice analytics of that kind is a quality-assurance tool, and a slow one. AI conversation analytics is a different proposition, because the agent already holds the transcript of every call rather than a sample of them.
An AI call analytics voice agent produces a complete record by default, so the denominator is real. Questions that were unanswerable at a five percent sample, such as how often callers ask about a product you stopped selling, become a straightforward count.
Voice AI call tracking joins the conversation to what happened next: booked, quoted, escalated, lost, no answer. Without that join you have call volume, which tells you how busy you were and nothing at all about whether it was worth it.
AI call reporting dashboards fail when they show volume and sentiment and stop there. The useful ones answer a question somebody was already asking on Monday morning, which is usually about missed calls, booking rate, or the topic that keeps needing a human.
Conversational AI analytics earns its place when it changes a decision. A trend in call reasons that justifies rewriting a page on your website, an hour of the day that justifies extending cover, a question that keeps escalating and should not have to. Reporting that only confirms what you already believed is decoration, however well it renders.
Key capabilities
A real-time view of volume, handle time, and outcomes.
Measures resolution and conversion by call type, not just totals.
Shows how many calls turn into appointments and leads.
Groups calls by why customers reached out.
Reveals busy times so staffing and outbound land right.
Share performance or drop the numbers into your own reviews.
How it works
Inbound and outbound calls flow into one place.
Each call is categorized by why the customer reached out.
Resolution, bookings, and conversion are measured by type.
Live dashboards and exportable reports show what's happening.
The problem
Turn every conversation into AI call analytics: calls handled, resolution rate, average handle time, peak hours, and outcomes by intent. Centricall's AI voice analytics and AI call intelligence surface the patterns behind your calls, and as an AI call analytics software layer, clear dashboards and exportable reports show exactly how your agent is performing.
Scope of work
Design
Connect
Launch
Support
How we work
Clear milestones, constant communication, and zero hand-waving, from first call to live system.
We map your call flows, tools, and goals, and define what a great call looks like.
01We craft the scripts and voice, then wire in your CRM, calendar, and databases with scoped access.
02We run simulated calls, refine the responses, and review security before anything goes live.
03We go live with monitoring in place, then tune the agent based on real calls.
04Works with your stack
Business benefits
Plan around real peak hours, not guesswork.
See which sources and intents actually convert.
Surface the calls most likely to close.
Use outcomes to refine what the agent says.
Catch drop-off points and fix them.
Use trends to plan capacity ahead of time.
Use cases
Real scenarios where Analytics does the work, from the first trigger to the outcome it drives.
Staffing backed by data
Know what's resolving
Aligned across the team
Industries
A voice agent that answers patient calls around the clock, booking and confirming appointments, handling intake, and triaging after-hours calls, compliance-minded throughout.
See how
A real estate AI voice agent and phone answering service that captures every lead call the moment it lands, qualifying buyers and sellers, booking property showings, fielding listing inquiries, and calling leads back so deals keep moving.
See how
A voice agent that answers client calls with care, handling account inquiries, booking appointments, sharing application status, sending payment reminders, and qualifying leads, compliance-minded throughout.
See how
A voice agent that fields order and returns calls 24/7, tracking shipments, processing returns and exchanges, confirming COD orders, and calling back abandoned carts.
See how
A voice agent that keeps freight moving, fielding shipment-status calls, scheduling deliveries, coordinating with drivers, and pushing order updates around the clock.
See how
A voice agent that handles member calls all day, booking and rescheduling classes, fielding membership inquiries, processing renewals, and following up with leads.
See how
A voice agent that moves candidates through faster, running first-round screening calls, scheduling interviews, answering application-status questions, and pre-qualifying applicants at volume.
See how
An AI receptionist for plastic surgery, cosmetic, and aesthetic clinics, answering consultation enquiries discreetly, booking and confirming appointments, and covering the line outside clinic hours.
See how
An AI voice agent for education providers and edtech platforms, answering admissions enquiries, qualifying prospective students, booking counsellor calls, and following up on applications at scale.
See howAnalytics + CRM
Analytics get sharper when call summaries and CRM data feed them. Together they tie every call to a contact, an outcome, and a dollar value.
See which calls became contacts, deals, and revenue.
Call summaries add context to every metric.
Focus on the numbers your team cares about.
Drop clean data into your own reviews and tools.
FAQ
Everything you need to know before we start working together.
Calls handled, resolution rate, average handle time, peak hours, and outcomes broken down by intent, the metrics that tell you how your phones are actually performing.
Yes. Calls are categorized by intent, so you can see the top reasons people reach out and how each type tends to resolve.
Yes. You can see peak hours and busy days at a glance, which makes staffing and outbound timing far easier to plan.
Yes. Outcome tracking shows resolution and conversion by call type, not just raw totals, so you know what's truly getting handled.
Yes. Reports are exportable so you can share performance across the business or drop the numbers into your own reviews.
Dashboards update in real time, so you're looking at what's happening on your phones now, not a stale snapshot.
Centricall pairs voice analytics AI with AI powered call intelligence in one place. As voice AI analytics software, it turns raw calls into decisions, which is what separates us from most AI-powered call analytics software providers.
Scalability in voice AI is not one number. Ask how many simultaneous calls the deployment is provisioned for, what happens at that ceiling (queue, degrade, or drop), and whether latency holds as volume climbs. A scalable voice AI solution answers the five hundredth concurrent call as quickly as the first; one that answers it slowly has not scaled, it has just failed more politely.
Webhooks for both inbound and outbound events, idempotent retries, structured call outcomes rather than raw transcripts, per-tenant credentials, and rate limits published rather than discovered in production. Ask to see the error contract, not just the happy path.
Steady-state volume is rarely the problem; concentrated peaks are. When comparing voice infrastructure providers on stability under enterprise workloads, ask for behaviour at peak concurrency rather than an average, and check whether speech recognition accuracy degrades under load as well as latency. We size deployments against your measured peak, not a headline figure.
There are no independent, standardised benchmarks in this category, and published vendor comparisons are almost always run by a vendor who wins them. The benchmark that matters is your own call set: take 100 real calls, run them, and count how many were completed without a human.
Through approved integrations agreed during setup, with an explicit scope for what the agent may read and write. For organisations that cannot let call data leave their environment, the platform can be deployed on-premise inside your own cloud account or data centre.
Get started
Book a discovery call and we’ll set it up around your calls , live in days, not months.
Book a discovery call