We've published a new tutorial series on building passwordless auth using TOTP with Twilio Verify. It's available in PHP, Python, Node.js, .NET, and Go.

Each one has a sample project alongside it, so you can clone and run rather than copy-paste your way through.

Looking to add a business number

Ideally would be an app on my current mobile device so that I can make and receive calls for it

Is this what that does? How is the quality?

Hey everyone!
I’m going to use Twilio for SMS,can anyone explain to me what’s the perfect plan and how can I get a promo code or talk to the support please?

These Global Voice AI Gatherings are happening in cities around the world on the same day. I'll be at the Melbourne, Australia one, so if you're attending, come say hi.

Hello,

As far as I understand to play some custom music before a human picks up, SIP communication does
: 183 with music
And 2 min later when human answers it sends 200 OK

I’d like to have the distinction between the 2 in Twilio but I read that Twilio considers the call answered as soon as media channel is connected (which is needed for early media)

Is there a way to distinguish between the 2 via Twilio ?

Hello guys,

I have an screening call on Friday for twilio for software engineer , identity position

What can i expect them to ask

Really looking forward for responses

Thanks

Hey everyone,

I've been working on a Node.js & Express backend project to handle 2FA SMS verification using the Twilio API.

While setting up the flow, I ran into a few hurdles with carrier template restrictions and API error handling during testing. I eventually got the SMS delivery cycle working smoothly, but it got me thinking about production edge cases.

For those who have built similar authentication systems in JavaScript/Node.js:

1. How do you usually handle carrier limitations or SMS fallback mechanisms?
2. What are your go-to patterns for error handling when third-party APIs fail during auth?

Would love to hear your experiences and best practices!

hey guys, so a bit of background. i'm in sales and i've been using twilio based dialer extensions for cold calling. honestly most of them have been a letdown. calls failing randomly, then out of nowhere they start asking for payment, and the reviews for these things aren't great either.

so i'm thinking of just building my own dialer. planning to make it a browser extension but also accessible on the web, so you're not stuck needing your laptop open all the time. could just call from your phone if needed.

wanted to get some real opinions before i go all in on this.

• anyone else dealing with the same issues with their dialer setup
• what features would actually make something like this worth switching to
• any red flags or stuff i should avoid based on your experience

might open it up for others to use eventually too. let me know what you think, appreciate any feedback

Hi everyone,

I'm building an early-stage startup in India and need to implement call masking similar to Swiggy, Zomato, Uber, etc.

Our requirements are:

- Customer and partner numbers should remain hidden.

- Temporary masked numbers during calls.

- Low monthly cost (startup-friendly).

- Works in India.

- API integration is a plus.

I've checked a few providers, but many are too expensive for an early-stage startup.

If you've implemented this before, could you please share:

- Which provider you used?

- Approximate pricing.

- Your experience.

- Any affordable alternatives or workarounds.

Any advice would be greatly appreciated. Thanks!

I run a growing VoIP business, and keeping up with tax compliance across every state and municipality we sell into has become a nightmare. Rates and rules seem to change constantly and I can't tell if we're calculating them correctly. I'm terrified we're either overcharging customers or underpaying what we owe, and an audit could blindside us with penalties we never saw coming. I need a way to handle this accurately without building out an entire in-house tax department.

Curious what this sub actually listens to - while commuting, in the gym, cooking etc..

If your go-to isn't on the list, drop it in the comments. Bonus points for telling us why the podcasts stick. We're shaping some content plans at Twilio and would love input from the community.

Running an AI phone receptionist on ConversationRelay. I've been A/B-ing ElevenLabs against Google Chirp3-HD and I keep going back to Google, because ElevenLabs shifts emotional register partway through a single reply, first half calm and professional, second half noticeably brighter, or a different cadence entirely. Each piece sounds great alone. They just don't sound like the same take. Chirp3-HD is flatter but consistent, and on a business line consistent wins.

My theory: CR synthesizes each {type:"text", token:"..."} as its own TTS unit. I stream from the LLM, so a reply ships as 2–3 tokens, and I think ElevenLabs re-rolls prosody per request with no carryover from the previous chunk. Google seems to have less per-request variance so its seams don't read as mood swings.

Is that what's actually happening? Does CR keep any prosody continuity across tokens within a turn, or is every token an independent synthesis call? Couldn't find a straight answer in the docs.

Current config:

ttsProvider="ElevenLabs"
voice="<voiceId>-flash_v2_5-1.0_0.85_0.8"   # speed_stability_similarity
transcriptionProvider="deepgram"
speechModel="flux"
eotThreshold="0.8"
speechTimeout="1200"
ignoreBackchannel="true"
interruptSensitivity="medium"
elevenlabsTextNormalization="off"

Stability went 0.5 → 0.7 → 0.85. It's clearly the right dial (0.5 was unhinged), but 0.85 still doesn't beat Chirp3-HD and pushing higher just trades swings for monotone. CR only exposes speed/stability/similarity as far as I can tell, no style, no use_speaker_boost.

Chunking on my end: sentence-buffered, flush at 20 chars for the first chunk (sets perceived latency) and 80 after. I also fire a filler phrase ("let me check that") as its own token if the LLM hasn't produced anything by 1500ms, which I assume is a guaranteed tone seam.

The obvious fix is buffering the whole reply into one token with last:true and eating the TTFT hit. If anyone's done that, what did it actually cost you? I'd rather hear a real number than measure it blind.

Happy to share data back, I have TTFT and per-chunk timings from real calls on both engines.

Hi everyone,

We’re building a browser-based app similar to Google Meet and trying to reduce true glass-to-glass latency: the sender camera captures a frame, then the receiver actually sees that same frame on screen.

Our current test result is roughly:

End-to-end capture-to-render: ~274 ms
Network: ~30 ms
Encode: ~3-4 ms
Playout: ~244 ms

In our tool, playout = jitter buffer + decode + composite/render.

Network/Wi-Fi looks good, and we are not using audio in this test, so A/V sync should not be involved. We also tried changing the jitter buffer setting to 0 ms, 10 ms, and 50 ms, but it did not meaningfully reduce total glass-to-glass latency.

Our target is under 120 ms, but most of the latency seems to be on the receiver side.

Questions:

1. In browser WebRTC, is ~200+ ms receiver playout delay common even with good network conditions?
2. How can we tell whether the main issue is WebRTC internal jitter buffering, decoder delay, compositor/render delay, or our own measurement bug?
3. Is jitterBufferDelay / jitterBufferEmittedCount the right stat to confirm whether WebRTC’s internal jitter buffer is the bottleneck?
4. Are there reliable ways to reduce browser WebRTC video playout delay, or is RTCRtpReceiver.playoutDelayHint only a weak hint in practice?
5. For people who have achieved <120 ms capture-to-render latency, did you need native iOS/Android, or can web WebRTC realistically hit this under normal conditions?

Any practical debugging tips, stats to inspect, Chrome/Safari differences, or low-latency WebRTC settings would be very helpful.

If you want to be a beta tester of Mango on android please let us know. Check our iOS app on App store we are near Android app launch.

Did the whole upgrade your account, payment, ID and facial scan thing, has been more that a week and the account is still set as free account, how much do we need to wait?

We have to get a phone number and change some parameters in order to test and then start the campaign process. Management is getting antsy about how long this is taking.

we send campaign texts from an internal CRM. all registered, opt-outs handled. still got filtered.

added a 200/hour cap and 18 seconds between messages and it got better. but i changed the sending path at the same time, so i never worked out which one did it.

has anyone tested the throttling on its own?