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ClawdTalk: Voice Calls for ClawdBots

Details

External ID
46947087
Source
HN
Company
—
Product
ClawdTalk: Voice Calls for ClawdBots
Website domain
clawdtalk.com
Launched
Feb. 9, 2026
Cohort
—
Upvotes
20
Upvotes percentile
0.6886792452830188
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

Hey HN, We built ClawdTalk to let AI agents operate over live phone calls.Most agents today live in chat windows. The moment you try to use them over voice, things break: latency matters, interruptions happen, and the agent has to execute tools while the conversation is still live.ClawdTalk connects your Clawdbot to the phone network. The agent gets a real phone number. It can make and receive calls and run the same tools it uses in chat, but under real-time voice constraints.One of the reasons this is hard is infrastructure. Many voice stacks stitch together separate telephony, speech, and model APIs. Each hop adds latency, and people report 8–30 second round trips.We got it under ~3 seconds by running the full voice path ourselves. Telnyx (my employer) is a telecom carrier, and we run PSTN, STT, and TTS on our infrastructure. No middlemen.How it works: 1. Connect your OpenClaw agent to ClawdTalk 2. We provision a phone number 3. Inbound/outbound calls route directly to the agent 4. The agent executes tools mid-conversationLimitations: 1. Latency still depends on your LLM (we control voice, not inference) 2. US numbers only for now (international coming) 3. Not a new agent framework (OpenClaw only today)Demo number: +1-301-MYCLAWD (692-5293) (call to talk to the agent) Happy to answer questions about the architecture or telephony side.

Enrichment

Theme
ai agents for calls and meetings
Vertical
Horizontal
Function
Communication
Audience
Developer
AI stance
AI feature
Project type
Hobby / open-source project
Normalized one-liner
voice calls for ai agents
Manually corrected
False

Could you build this?

Partial Connecting an LLM to telephony can be quickly prototyped using APIs like Twilio and LiveKit, but maintaining low-latency bidirectional streaming, interruptibility (barge-in), and mid-call tool execution requires specialized voice pipeline engineering. Pure vibe coding typically falls short on deterministic real-time audio orchestration and edge latency tuning.

What it would actually take: A viable voice-agent platform uses WebRTC/SIP backends (e.g., LiveKit, Daily, or Asterisk) integrated with low-latency Speech-to-Text (Deepgram), an LLM streaming bridge, and Text-to-Speech (Cartesia, ElevenLabs). The critical challenge is building a high-performance audio arbiter that handles Voice Activity Detection (VAD), instant barge-in cutoffs, and asynchronous tool invocation without causing perceptual pauses or audio stuttering. This requires expertise in real-time media streaming, jitter buffer management, and websocket concurrency.

Discussion

No comments on this launch.

Competitors

Other products that read as similar to this one — 151 launches clear the similarity bar, closest 8 shown.

Attention rank: #59 of 152 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 94 days after the earliest competitor.

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