Traditional IVR routes callers through a fixed decision tree of button presses, so anything outside the script trips it up (“I’m sorry, I didn’t understand that”). Quiq’s Voice AI listens for what the customer actually needs and works from Process Guides, plain-language operating procedures that adapt in the moment rather than a rigid script. If a caller goes off-script, the AI reroutes toward resolution instead of breaking. It also carries context across channels: a caller can get a text mid-call with photos or a booking confirmation and pick the conversation back up on the phone without repeating themselves.

Yes. Quiq’s Voice AI is built to complete multi-step tasks end to end, things like rebooking a flight, updating an account, or walking through a troubleshooting flow, without handing the caller off. It applies your business rules the way a well-trained agent would: checking eligibility, confirming details, and taking the action, all inside a single call. Leading brands using Quiq’s Voice AI report saving $262 per customer as a result. When a call genuinely needs a human (an edge case outside policy, an upset customer), it escalates with full context intact, so nothing gets re-explained.

The conversation just continues. If a claim needs photos, Quiq can send a text mid-call so the customer can snap a picture and text it back, without hanging up, calling back, or repeating the story to a new person or system. This is the same continuous-context architecture behind every Quiq product, so a voice call can shift to SMS, WhatsApp, or web chat and back again without losing any detail. Other platforms treat channel switching as a hard reset. Quiq treats it as one ongoing thread.

Every decision the Voice AI makes is logged in a decision tree you can review step by step: what it checked, what policy it applied, and why it took the action it did. You set the guardrails it operates within, and Quiq’s Verify Claim feature cross-references every response against your trusted data before it reaches a customer, catching problems before they become a compliance issue. That combination, configurable guardrails plus a full audit trail, is what lets enterprises hand voice conversations to AI without losing the ability to see, and fix, exactly what it’s doing.

A proof of concept typically takes 2 to 4 weeks using your actual call data, so you can hear how it performs before committing further. Most teams move to a pilot within 1 to 2 months, and full production rollout typically lands in the 3 to 6 month range depending on complexity and how many systems it needs to connect to. Because Process Guides are written in plain language rather than trained through months of model fine-tuning, updates and new use cases can usually be added in weeks rather than requiring a new development cycle.

PolyAI focuses specifically on voice, so if you need a unified experience across chat, SMS, or WhatsApp too, you’re stitching together a separate platform. Sierra and similar AI layers sit on top of your existing channels but don’t own them outright, meaning your voice, messaging, and human agent workspace can end up feeling like three different products wearing one logo. Quiq is a full-stack platform: voice, SMS, WhatsApp, and chat are native to one system, along with the agent workspace and analytics, so a single conversation can move across every channel without losing context. For a closer look at a specific competitor, see Quiq’s comparison pages, for example Quiq vs. Sierra AI and Quiq vs. Poly AI