u/Slight_Republic_4242

So here's probably the craziest thing you will come across today:

First lets admit we all know the hardest part isn't building anymore-it's distribution and getting seen.
Its honestly become atleast 5x harder to get any traffic.
I counted 535 new product launches on Product Hunt on 2nd July (there were more products- just stopped scrolling after that)

Paid ads are rent and CAC is brutal right now - but what if we helped each other grow?

In my previous startup, traffic swaps with complementary companies became one of our biggest growth levers- and eventually got acquired.
All inspired by this YC founder who scaled to 25M. 

I have done the same twice now-  Last time, just a few months back with a closed group of top founders.
Traffic swaps, launch support and backlinks with complementary companies.

See it for yourself- open Google/Gemini and search "oss voice ai platform" (open in incognito,else biased by your history).
-The first LLM recommendation is our company, Dograh.
-The top YouTube video is about Dograh
- The top blog is about Dograh.
-The top Reddit post
- the top recommended link by AI
..you get it.

And now we are #1 Product hunt

We started Dograh out of rage - an open-source voice AI platform.

Every voice AI tool I tried was too costly, too closed, or too scammy. Add-on stacked on add-ons.

So we open-sourced every single line, from day 0. Self-hostable, so you own your stack and your data.

Here's what pushed me deeper. Over the last few months, the big labs have been lobbying governments to ban open source. Some say the quiet goal is to "let wealth access skill without letting skill access wealth." That line stuck with me. It's exactly why we keep going.

Because we believe one thing: no company should own voice AI.

We're a small team no funding going up against deeply funded war chests. Today we launched on Product Hunt and somehow we're sitting at #1 so far.

A community member picked us up few weeeks back and we went viral and hit 5k stars.

About me: I'm a YC alum, founder with one exit, and an angel. I'll keep going - we’ll address OSS ban with more open source.

https://www.producthunt.com/posts/dograh-3

If you've got a minute, a star or a feedback would mean the world.

We started Dograh out of rage - an open-source voice AI platform.

Every voice AI tool I tried was too costly, too closed, or too scammy. Add-on stacked on add-ons.

So we open-sourced every single line, from day 0. Self-hostable, so you own your stack and your data.

Here's what pushed me deeper. Over the last few months, the big labs have been lobbying governments to ban open source. Some say the quiet goal is to "let wealth access skill without letting skill access wealth." That line stuck with me. It's exactly why we keep going.

Because we believe one thing: no company should own voice AI.

We're a small team no funding going up against deeply funded war chests. Today we launched on Product Hunt and somehow we're sitting at #1 so far.

A community member picked us up few weeeks back and we went viral and hit 5k stars.

About me: I'm a YC alum, founder with one exit, and an angel. I'll keep going - we’ll address OSS ban with more open source.

https://www.producthunt.com/posts/dograh-3

If you've got a minute, a star or a feedback would mean the world.

We started Dograh out of rage - an open-source voice AI platform.

Every voice AI tool I tried was too costly, too closed, or too scammy. Add-on stacked on add-ons.

So we open-sourced every single line, from day 0. Self-hostable, so you own your stack and your data.

Here's what pushed me deeper. Over the last few months, the big labs have been lobbying governments to ban open source. Some say the quiet goal is to "let wealth access skill without letting skill access wealth." That line stuck with me. It's exactly why we keep going.

Because we believe one thing: no company should own voice AI.

We're a small team no funding going up against deeply funded war chests. Today we launched on Product Hunt and somehow we're sitting at #1 so far.

A community member picked us up few weeeks back and we went viral and hit 5k stars.

About me: I'm a YC alum, founder with one exit, and an angel. I'll keep going - we’ll address OSS ban with more open source.

Roast it if you can!!

We started Dograh out of rage - an open-source voice AI platform.

Every voice AI tool I tried was too costly, too closed, or too scammy. Add-on stacked on add-ons.

So we open-sourced every single line, from day 0. Self-hostable, so you own your stack and your data.

Here's what pushed me deeper. Over the last few months, the big labs have been lobbying governments to ban open source. Some say the quiet goal is to "let wealth access skill without letting skill access wealth." That line stuck with me. It's exactly why we keep going.

Because we believe one thing: no company should own voice AI.

We're a small team no funding going up against deeply funded war chests. Today we launched on Product Hunt and somehow we're sitting at #1 so far.

A community member picked us up few weeeks back and we went viral and hit 5k stars.

About me: I'm a YC alum, founder with one exit, and an angel. I'll keep going - we’ll address OSS ban with more open source.

If you've got a minute, a feedback would mean the world.

We started Dograh out of rage - an open-source voice AI platform.

Every voice AI tool I tried was too costly, too closed, or too scammy. Add-on stacked on add-ons.

So we open-sourced every single line, from day 0. Self-hostable, so you own your stack and your data.

Here's what pushed me deeper. Over the last few months, the big labs have been lobbying governments to ban open source. Some say the quiet goal is to "let wealth access skill without letting skill access wealth." That line stuck with me. It's exactly why we keep going.

Because we believe one thing: no company should own voice AI.

We're a small team going up against deeply funded war chests. Today we launched on Product Hunt and somehow we're sitting at #1 so far.

A community member picked us up few weeeks back and we went viral and hit 5k stars.

About me: I'm a YC alum, founder with one exit, and an angel. I'll keep going - we’ll address OSS ban with more open source.

https://www.producthunt.com/posts/dograh-3

If you've got a minute, a star or a bit of support would mean the world.

I'm Pritesh Kumar, an exit founder, YC alum, and now co-founder of Dograh, an open-source voice AI agent platform. Dograh has trended on GitHub several times; it's one of the most popular open-source voice agents out there, and our daily signups grew 20x in the last two weeks, all organic, zero ad spend.

The conversation I bring isn't the usual hype reel. I build this tech for a living, so I can talk honestly about where voice AI actually helps and where it falls apart, and why we open-sourced our infrastructure.

It's really a conversation about who owns AI. The most powerful models stay locked behind closed platforms, and builders should own their stack. Voice AI is the lens, but the argument travels much further: open source, ownership, and honesty in a space full of hype.

I'd be a great fit for shows on AI automation, voice AI, startups, and entrepreneurship. I talk straight and unscripted, no rehearsed takes. If you host conversations that go somewhere unexpected, drop a comment or DM me.

Hey everyone,

Speech-to-speech is the next big thing in the Voice AI, and the performance differences from traditional cascade (STT for transcription, LLM for reasoning, TTS for the voice output) pipelines are huge. I have been using both for months. And I  wonder why people still default to the old way.

With the old way, it went speech to text, then LLM, then text to speech. The pause before every reply just killed the flow. First, it waits for the transcript, then it waits for the LLM to think, then it waits for the voice to start. Three separate waits for one answer. However, we can reduce some of this delay with workarounds like pre-recorded audio, caching common responses, and prompt optimization. But the latency is still high.

Long conversations can also make the voice drift and feel less natural.

Then I tried speech-to-speech with GPT Realtime 2 and Gemini 3.1 live. 

The reply time dropped to about half.

The model follows your prompt instructions better in a long conversation

It has multilingual support, and we can switch languages mid-conversation very well based on user input. 

 The speech-to-speech interaction feels far more natural than the typical STT/  TTS pipeline. 

The bot keeps the same voice and personality even on long calls

It works best for angry support calls, outbound sales, mixed language conversations, and scheduling bots where users change their minds mid-sentence.

And in the longer run, I think speech-to-speech will end up cheaper than the cascade approach.

If you want to try speech-to-speech without setting up the whole orchestration yourself, we built Dograh. It is an open-source voice agent platform that supports both cascade and speech-to-speech models. You can take any agent flow you build, run it once with cascade and once with speech to speech, and feel the difference in how it behaves, the latency, and how it handles emotions.

Has anyone else moved to speech-to-speech? Worth it or not?

Hey everyone,

Speech-to-speech is the next big thing in the Voice AI, and the performance differences from traditional cascade (STT for transcription, LLM for reasoning, TTS for the voice output) pipelines are huge. I have been using both for months. And I  wonder why people still default to the old way.

With the old way, it went speech to text, then LLM, then text to speech. The pause before every reply just killed the flow. First, it waits for the transcript, then it waits for the LLM to think, then it waits for the voice to start. Three separate waits for one answer. However, we can reduce some of this delay with workarounds like pre-recorded audio, caching common responses, and prompt optimization. But the latency is still high.

Long conversations can also make the voice drift and feel less natural.

Then I tried speech-to-speech with GPT Realtime 2 and Gemini 3.1 live. 

The reply time dropped to about half.

The model follows your prompt instructions better in a long conversation

It has multilingual support, and we can switch languages mid-conversation very well based on user input. 

 The speech-to-speech interaction feels far more natural than the typical STT/  TTS pipeline. 

The bot keeps the same voice and personality even on long calls

It works best for angry support calls, outbound sales, mixed language conversations, and scheduling bots where users change their minds mid-sentence.

And in the longer run, I think speech-to-speech will end up cheaper than the cascade approach.

If you want to try speech-to-speech without setting up the whole orchestration yourself, we built Dograh. It is an open-source voice agent platform that supports both cascade and speech-to-speech models. You can take any agent flow you build, run it once with cascade and once with speech to speech, and feel the difference in how it behaves, the latency, and how it handles emotions.

Has anyone else moved to speech-to-speech? Worth it or not?

Hey everyone,

Speech-to-speech is the next big thing in the Voice AI, and the performance differences from traditional cascade (STT for transcription, LLM for reasoning, TTS for the voice output) pipelines are huge. I have been using both for months. And I  wonder why people still default to the old way.

With the old way, it went speech to text, then LLM, then text to speech. The pause before every reply just killed the flow. First, it waits for the transcript, then it waits for the LLM to think, then it waits for the voice to start. Three separate waits for one answer. However, we can reduce some of this delay with workarounds like pre-recorded audio, caching common responses, and prompt optimization. But the latency is still high.

Long conversations can also make the voice drift and feel less natural.

Then I tried speech-to-speech with GPT Realtime 2 and Gemini 3.1 live. 

The reply time dropped to about half.

The model follows your prompt instructions better in a long conversation

It has multilingual support, and we can switch languages mid-conversation very well based on user input. 

 The speech-to-speech interaction feels far more natural than the typical STT/  TTS pipeline. 

The bot keeps the same voice and personality even on long calls

It works best for angry support calls, outbound sales, mixed language conversations, and scheduling bots where users change their minds mid-sentence.

And in the longer run, I think speech-to-speech will end up cheaper than the cascade approach.

If you want to try speech-to-speech without setting up the whole orchestration yourself, we built Dograh. It is an open-source voice agent platform that supports both cascade and speech-to-speech models. You can take any agent flow you build, run it once with cascade and once with speech to speech, and feel the difference in how it behaves, the latency, and how it handles emotions.

Has anyone else moved to speech-to-speech? Worth it or not?

Hey everyone,

Speech-to-speech is the next big thing in the Voice AI, and the performance differences from traditional cascade (STT for transcription, LLM for reasoning, TTS for the voice output) pipelines are huge. I have been using both for months. And I  wonder why people still default to the old way.

With the old way, it went speech to text, then LLM, then text to speech. The pause before every reply just killed the flow. First, it waits for the transcript, then it waits for the LLM to think, then it waits for the voice to start. Three separate waits for one answer. However, we can reduce some of this delay with workarounds like pre-recorded audio, caching common responses, and prompt optimization. But the latency is still high.

Long conversations can also make the voice drift and feel less natural.

Then I tried speech-to-speech with GPT Realtime 2 and Gemini 3.1 live. 

The reply time dropped to about half.

The model follows your prompt instructions better in a long conversation

It has multilingual support, and we can switch languages mid-conversation very well based on user input. 

 The speech-to-speech interaction feels far more natural than the typical STT/  TTS pipeline. 

The bot keeps the same voice and personality even on long calls

It works best for angry support calls, outbound sales, mixed language conversations, and scheduling bots where users change their minds mid-sentence.

And in the longer run, I think speech-to-speech will end up cheaper than the cascade approach.

If you want to try speech-to-speech without setting up the whole orchestration yourself, we built Dograh. It is an open-source voice agent platform that supports both cascade and speech-to-speech models. You can take any agent flow you build, run it once with cascade and once with speech to speech, and feel the difference in how it behaves, the latency, and how it handles emotions.

Has anyone else moved to speech-to-speech? Worth it or not?

Hey everyone,

We just shipped Speech-to-Speech model support across Dograh. You can now build voice agents on Gemini 3.1 Flash Live, Vertex Live, OpenAI GPT-Realtime-2, and other S2S models, the same way you'd build them on the older STT-LLM-TTS pipeline.

Why we built this:

Most voice AI platforms still run the same pipeline: STT, then the model responds in text, then TTS turns it back into audio. 

It works, but on real calls, the problems show up fast. There's a small delay before each reply. Interruptions feel awkward. On longer calls, the voice drifts and starts feeling less natural.

The newer Realtime models remove the pipeline. They process audio directly. You stream audio in, and the model streams audio back out.

To test this, we built a real-time voice agent using this model.  

What stood out on real calls:

• Interruptions feel more natural, and the agent reacts the way a person would
• Voice persona stays consistent in long sessions
• Switching languages mid-call works without a separate routing layer
• Responses feel faster because the extra pipeline is gone

The setup stays simple but works well for support bots, AI calling, scheduling assistants, and multilingual voice agents.

We've been building Dograh quietly for many months now. Open-source voice AI platform. Small team. No big launches, no marketing budget, just shipping code and hoping it would matter to someone.

Today our GitHub stars started climbing fast. We were confused. We checked our homepage, where a small bot asks new users how they found us, and almost everyone was saying YouTube. We searched and found a tutorial from BetterStack, posted about an hour ago. They built something with Dograh, liked it enough to record a video, and put it out into the world. We've never spoken to them. We never asked.

First time crossing 500 stars. 80+ in the last few hours alone.

I've been sitting here just looking at the signup graph for a while. It's been a long time since I felt this kind of happiness about the project. The kind that creeps up slowly and then you realize you're smiling at your laptop like a kid.

Biggest takeaway: if your thing solves a real problem, people will market it for you. You just have to keep building it until they find it. 

Reminds me of my YC days- they used to say Build something people want.

A few months ago I told my co-founder I wasn't sure if anyone would ever care about what we were building.

We started Dograh as an open-source voice AI platform. Alternative to the closed players like Vapi and Retell. We thought developers would want this. But for a long time, GitHub stars trickled in slowly. Discord stayed quiet. Some days I'd refresh the analytics dashboard hoping to see something move, and nothing would.

Today everything changed. 

Our stars started climbing fast and we couldn't figure out why. Then we looked at our homepage bot, which asks every new user where they heard about us. Almost all of them said YouTube. We searched and found a tutorial from BetterStack, posted an hour ago. They'd built something with Dograh, liked it enough to record a video, and put it out into the world. We had no idea it was coming. We've never spoken to them.

We just crossed 500 stars. I keep refreshing the signup graph because part of me still doesn't believe it.

If you're building something open source and the silence is getting to you, I just want to say: someone out there might already be using your project. They might be about to tell the world. Keep shipping.

Hey Everyone,

We spent 9 months building Dograh, an open-source voice agent platform. Before building this, we researched everything about voice AI, starting with YouTube tutorial recommendations, and also looked at other competitors like Vapi, Pipecat, and Retell, to know what the industry is facing as a major problem, and how we can build the best OSS voice AI builder platform. 

As we slowly started building, we realized that making agents is easy, but the benchmark is not a chatbot; it's a human. People judge based on whether it feels natural, like a human or not. People always notice the 5% where AI sounds off. Even LLMs are powerful but still unpredictable. Managing expectations is harder than building the agent. Voice quality will make or break everything.

We tried to solve a lot of these problems. For example, you can use a pre-recorded voice for a more natural feel and reduced latency, and we also integrated a speech-to-speech model.

We just released a new feature where you can use it with OpenClaw or Claude Code- recently launched MCPs.

Apart from this, we added a lot of features to the open source, like telephony (Twilio, Plivo, SIP), call analytics, knowledge base, CRM connectors, and BYOK for any LLM, STT, or TTS.

A few questions for this community:

What are the most interesting features you find in other platforms today?

Github: https://github.com/dograh-hq/dograh