Most AI phone tools are built for enterprises — APIs, workflows, sales automation. PollyReach is built for you. Give your AI a real phone number. Say "book me a table for 7pm" — it finds the number, makes the call, handles the conversation, and reports back with a summary, recording & transcript. It also answers your phone 24/7 and screens spam. Works in 50+ languages.
The detail that stood out to me is your note that pronunciation gets spotty on long number sequences. I build voice AI for daily check-in calls with aging parents, and our toughest problem sits at the other end of that: older callers speak slowly and pause mid-sentence, so aggressive endpointing makes the agent talk over them. How are you tuning silence thresholds and barge-in timing so Polly waits long enough without feeling laggy? Curious whether you landed on a fixed VAD window or something adaptive per caller.
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The failed-call and guardrail threads are well covered, so a different one: confirmation integrity. When Polly mishears 7:45 as 7:00, I only find out when I show up. Do you capture an explicit readback the callee agrees to and make that the source of truth in the summary, rather than Polly's own interpretation of the call? And as more businesses run their own AI receptionists, you hit agent-to-agent calls where intent gets serialized to speech and back twice. Any plan for a text or MCP fast-path when the other side is also a bot?
@krouton We have received feedback from multiple users and are currently preparing this feature. It is already on our roadmap, and we will notify everyone once it's ready!
Interesting idea. Giving an AI agent a real phone number could be really useful for booking, call screening, and handling routine phone tasks. Curious how you handle privacy, consent, and call quality across different languages.
@julie_su We take privacy and compliance strictly first. All call data is end-to-end encrypted, conversations won’t be leaked or misused. We strictly follow regional call recording consent rules automatically.
@nisa_meray Polly is designed for task-oriented conversations and prepares specific talking points in advance. Because of this, we have a mechanism in place to end the dialogue if it start to become negative or unproductive.
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How does it handle edge cases like being put on hold for 10+ minutes, or when someone asks "can I speak to a manager"?
@boyuan_deng1 Our system is well optimized for various real-call edge scenarios.
Long hold over 10 minutes
It can automatically detect the hold status, keep the call line stable without accidental disconnection, and maintain standby state patiently. It will resume normal conversation immediately once the other party picks up again.
Request to speak to a manager
Built-in rich business dialogue templates and flexible response logic support instant natural replies to such requests. It can smoothly respond accordingly, transfer the conversation direction reasonably, or follow preset strategies to continue effective communication as needed.
All unexpected daily conversation scenarios are fully covered to ensure smooth and natural calling interaction.
Refocus
The detail that stood out to me is your note that pronunciation gets spotty on long number sequences. I build voice AI for daily check-in calls with aging parents, and our toughest problem sits at the other end of that: older callers speak slowly and pause mid-sentence, so aggressive endpointing makes the agent talk over them. How are you tuning silence thresholds and barge-in timing so Polly waits long enough without feeling laggy? Curious whether you landed on a fixed VAD window or something adaptive per caller.
The failed-call and guardrail threads are well covered, so a different one: confirmation integrity. When Polly mishears 7:45 as 7:00, I only find out when I show up. Do you capture an explicit readback the callee agrees to and make that the source of truth in the summary, rather than Polly's own interpretation of the call? And as more businesses run their own AI receptionists, you hit agent-to-agent calls where intent gets serialized to speech and back twice. Any plan for a text or MCP fast-path when the other side is also a bot?
Does this have 'Hindi' language support ?
PollyReach
@gajendra_singh20 Yes, Hindi is supported. Would love to hear your feedback after trying it out 🙌
PollyReach
@gajendra_singh20 Yes
PollyReach
@krouton We have received feedback from multiple users and are currently preparing this feature. It is already on our roadmap, and we will notify everyone once it's ready!
Paraflow
Interesting idea. Giving an AI agent a real phone number could be really useful for booking, call screening, and handling routine phone tasks. Curious how you handle privacy, consent, and call quality across different languages.
PollyReach
@julie_su We take privacy and compliance strictly first. All call data is end-to-end encrypted, conversations won’t be leaked or misused. We strictly follow regional call recording consent rules automatically.
PollyReach
@julie_su We take user privacy and security very seriously. Regarding language support, we currently offer more than 50 different languages.
Spiky
Hi! How does Polly handle conversations that start to become negative or unproductive?
PollyReach
@nisa_meray Polly has built-in sentiment detection to manage negative & unproductive chats smartly
PollyReach
@nisa_meray Polly is designed for task-oriented conversations and prepares specific talking points in advance. Because of this, we have a mechanism in place to end the dialogue if it start to become negative or unproductive.
How does it handle edge cases like being put on hold for 10+ minutes, or when someone asks "can I speak to a manager"?
PollyReach
@boyuan_deng1
Our system is well optimized for various real-call edge scenarios.
Long hold over 10 minutes
It can automatically detect the hold status, keep the call line stable without accidental disconnection, and maintain standby state patiently. It will resume normal conversation immediately once the other party picks up again.
Request to speak to a manager
Built-in rich business dialogue templates and flexible response logic support instant natural replies to such requests. It can smoothly respond accordingly, transfer the conversation direction reasonably, or follow preset strategies to continue effective communication as needed.
All unexpected daily conversation scenarios are fully covered to ensure smooth and natural calling interaction.