Enterprise AI bot detection for contact centers

Your real customers are stuck behind bots

High-volume bot traffic jams the voice channel, stretches handle times, and pushes real callers down the queue. The Pindrop BotStopper™ helps identify automated callers in seconds, so your agents spend their time on real people.

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  • 0%

    Drop in bot calls at a healthcare org1

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    False positives2

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    To assess a call for synthetic activity

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AI BOT DETECTION

What is AI bot detection for contact centers?

AI bot detection identifies synthetic and automated callers. It can help separate three things your contact center handles differently: a legitimate AI agent calling on a customer's behalf, nuisance automation clogging the queue, and a malicious bot probing your defenses.

Most contact centers were built on an assumption that no longer holds: that the voice on the line belongs to a human. Your IVR can't tell the difference between a customer who forgot their PIN and an AI bot conducting reconnaissance. And neither can your contact center agents.

BotStopper doesn't wait for a bot to act. It scores every caller as it comes in, so you can reroute, challenge, or block before an agent picks up.

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94.3% fewer bot calls in six months
See how a healthcare contact center identified 30,000+ bot calls in under a year.

BOT AND AGENTIC TRAFFIC MANAGEMENT

How does Pulse make bots visible in real time?

Most contact centers need bot detection urgently. Pulse scores callers inside your call flows, answering the question "was that a real person?" right when you need it.

In your existing call flow

Pulse integrates with leading CCaaS providers, so scoring happens inside your IVR and agent workflows instead of requiring your team to pull recordings into a separate tool after the fact.

Analysis runs in real time

Pulse evaluates live call audio for indicators of synthetic speech, cloned voices, and known AI generation engines. Every call receives a liveness score after roughly two seconds of speech, and analysis continues as the call progresses.

Your policy decides what happens next

When Pulse flags synthetic activity, that context surfaces in the workflow while the call is still live. You decide what follows: route the caller out of self-service, add additional verification, or send the call to review.

Add continuous bot detection to the contact center platform you already use

Pulse is designed to work with common enterprise contact center platforms, so you don't have to rebuild your call flow or retrain your agents. Here's what to consider when looking for a bot detection solution.

01

Coverage

Where scoring begins and which IVR and agent stages it covers.

02

Output

Which systems consume the risk score

03

Triggers

What each risk level triggers under your approved policies.

Defend your most targeted call flows

Bot traffic concentrates in your highest-risk workflows—the flows that reset access, move money, or expose data without a human in the loop.

Use case

IVR self-service and account recovery
Password resets and PIN changes are exactly when a bot can reach real access with no agent involved. Analyzing the caller for synthetic activity before the reset means self-service stays fast for the people who need it.

Use case

Patient and member verification
Attackers can easily send thousands of bots to test workflows and get access to sensitive data like PHI. Knowing that a bot is reaching a verification workflow helps you better defend the sensitive data behind it.

Use case

Payments and high-value authorizations
Bots look for weaknesses wherever money moves, trying to initiate transfers or payments at volume. Bot detection helps flag those high-value transactions before the loss happens.

INDUSTRY

Subscriptions, downgrades, and cancellations
Bot-driven downgrades and cancellations drain revenue, and high-volume automation jams the same contact center your customers depend on. Separating automated callers from real customers defends both revenue and experience.
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Article

Learn how audio deepfake detection works

Go deeper on how audio deepfakes are created, the signals detection systems evaluate, where audio detection can fall short, and how organizations can build a layered response. The article provides the educational context behind the enterprise audio deepfake detection solution.

CUSTOMER OUTCOMES

Bot detection at work

See how real-time analysis of the voice channel helps organizations make more informed decisions about who reaches an agent.

A Fortune 500 org shut down 94.3% of bot attacks with Pindrop

This organization needed a way to handle high volumes of bot attacks. Once Pindrop solutions made them visible, the team responded—and attacks became less productive and volume declined.

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HealthEquity reduced fraud by more than 90%

HealthEquity layered Pindrop risk analysis into its contact center ecosystem to passively analyze callers and risk signals. The result? A drastic reduction in voice fraud.

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Michigan State University Federal Credit Union cut $2.57M+ in fraud exposure

During its first year with Pindrop, MSUFCU reported that Protect helped stop more than $2.57 million in potential losses and identify more than 220 fraudulent calls.

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Don’t assume. Verify.

Take the first step toward a safer, more secure future for your business.

Schedule a demo

AI bot detection software FAQs

Get direct answers to common questions about how AI bot detection works in the contact center, where it fits, and what to evaluate.
What is an AI bot in the contact center?
How is an AI bot different from a robocall?
Is all bot traffic malicious?
Does Pindrop block every AI bot call?
How fast is detection?
Will this create false positives for real customers?

Disclaimer

Sources