Zinley vs Presto Voice

What users praise

• • Giving the AI its own phone number builds a trust boundary — the core differentiator.
• • The own-number approach avoids impersonating the user, addressing key trust concerns.
• • Handles calls, email, and tasks proactively, reducing friction for busy professionals.
• • The ability to set permission levels per contact is a highly requested feature.

What frustrates them

• • Critical question: are callers told they're speaking to an AI?
• • Caller-ID spoofing could trick the AI — a real security gap.
• • Relationship-graph data storage and retention are undocumented, raising privacy fears.
• • No public pricing or integration details — hard to justify the investment blind.

What users praise

• • Fifteen-plus years in restaurant automation gives Presto real QSR operational experience
• • Handles POS and headset provider integration itself, avoiding a lane shutdown at install
• • National rollouts at Wienerschnitzel, Taco John's, and Dairy Queen validate enterprise scale
• • Spectrum-of-models approach targets store-by-store variation in menus, accents, and ambient noise

What frustrates them

• • No independent operator reviews exist in the public data to validate the 95% claim
• • Vendor-published metrics lack third-party audited baselines or methodology
• • Only Toast is named as an integration — other POS stacks are unproven
• • Pricing is undisclosed, making per-lane ROI modeling impossible up front