DialpadPaid
An AI-native business phone and contact center where transcription, coaching, and autonomous voice agents run on the same call the humans are on.
Communication comparison
Pricing, pros, cons, and ideal use cases — side by side.
An AI-native business phone and contact center where transcription, coaching, and autonomous voice agents run on the same call the humans are on.
A shared business phone number for small teams, with an AI agent named Sona that answers calls around the clock on every plan.
| Dialpad | Quo (formerly OpenPhone) | |
|---|---|---|
| Pricing | PaidStandard starts at $15/user/month on annual billing (roughly $27 month-to-month); Pro is reported at around $25/user/month annual, and Enterprise is quoted. Dialpad's own site publishes the $15 entry point but not the full ladder. Dialpad AI Agents are billed separately on conversation-based AI Agent credits rather than per seat — model that line item before you sign. 14-day free trial. | PaidStarter $19/user/month monthly, $15 annual. Business $33/month, $23 annual. Scale $47/month, $35 annual. The Sona AI agent is included on all plans with 1,000 automation credits per month (roughly 10 calls); AI call summaries and transcripts cover Sona-handled calls on Starter and all calls on Business and Scale. AI call tagging is Scale-only. |
| Category | Communication | Communication |
| Ideal for | Businesses replacing an aging VoIP or PBX systemSales teams that want live call coaching, not just recordingsSupport teams consolidating phone, chat, and AI into one contact centerMulti-site SMBs that need one number plan across locations | Solo operators and teams under about 20 peopleBusinesses that run on texting as much as callingAgencies and consultancies needing a shared client-facing numberAnyone who wants published pricing instead of a demo call |
Dialpad is built around businesses replacing an aging voip or pbx system; Quo (formerly OpenPhone) leans more toward solo operators and teams under about 20 people. Shortlist the one whose strengths line up with your biggest constraint.
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