u/Electronic_Argument6

We’ve built what is essentially a full real-time telephony conversational operating system, not just a chatbot, and we’re trying to diagnose where our biggest failures actually are.

What we built:

A live voice pipeline for outbound/inbound calls:

Telephony (8kHz µ-law) → PCM decode → VAD → Silence thresholds → Echo suppression / AEC → STT (Deepgram/Groq/Sarvam) → Validation / hallucination filters → State machine → LLM (Groq LLaMA) → TTS (Grok) → Playback

Current capabilities:

Real-time Hindi + Hinglish support

Sales / lead-gen / support agents

Silero VAD

Deepgram Nova-3 primary STT

Groq LLaMA 3.x

Grok TTS

Barge-in

Sentence streaming

TTS cache

Carrier suppression

Hallucination filtering

Hindi grammar / transliteration optimization

Pipecat-style orchestration

FAISS RAG

The problem:

Users often feel like:

“The AI forgot what I said”

or

“It stopped responding”

or

“It heard me but replied weirdly”

But from logs, the LLM itself is often fine.

What we’re seeing:

STT:

Hindi strong

Hinglish moderate

Brand/model names weak

Short acknowledgements (“haan”, “ji”) vulnerable

Some blank transcripts / segmentation misses

TTS:

Biggest bottleneck

1.1–2.4s latency

“Response ended prematurely”

Long Hindi promotional lines degrade badly

Pipeline suspicion:

We may have over-engineered thresholds:

VAD

RMS gates

Silence windows

Echo suppression

Carrier suppression

Hallucination filtering

Confidence thresholds

Our current hypothesis:

This may not be a memory problem.

It may be a pipeline integrity problem where user intent is getting:

Clipped before STT

Mis-segmented

Filtered out

Suppressed during state transitions

Corrupted before conversational memory ever forms

Example:

Caller says a short Hindi response during suppression or barge-in window → speech never becomes canonical transcript → LLM never truly receives it → AI appears forgetful.

Questions for people who’ve built production voice stacks:

  1. Where do advanced telephony systems most commonly lose conversational fidelity?

VAD?

Endpointing?

Suppression windows?

STT confidence gates?

State machine transitions?

  1. For Hindi/Hinglish specifically:

How are people handling:

Short acknowledgements

Code-switching

Brand names

Telecom narrowband degradation?

  1. Would you simplify the stack?

Are we harming reliability by stacking too many protections before STT?

  1. TTS:

Would you prioritize:

Faster lower-quality speech

Smaller sentence chunks

Interruptibility

over polished voice quality?

  1. Architecture:

At what point does “production safety” become “signal destruction”?

Brutal honesty welcome:

If this architecture sounds overbuilt, fragile, or fundamentally mis-prioritized, I’d genuinely love to hear it.

We’re trying to move from:

“Smart AI on a fragile phone line”

to:

“Reliable conversational telecom system”

Right now it feels like our AI may actually be smarter than the user experience — but too much user intent dies before intelligence can act.

Would really appreciate insights from:

Voice AI engineers

Contact center architects

Telecom DSP people

Deepgram / Whisper / Pipecat builders

Hindi ASR/TTS teams

Thanks — looking for architecture-level criticism, not just model suggestions.

reddit.com
u/Electronic_Argument6 — 24 hours ago

We’re One Bug Away From Launching Our Voice AI Startup and Nobody Can Figure Out What’s Breaking

Hey everyone,

We’ve been building a real-time AI voice agent for the last 4 months and we’re finally in the final stages. The frustrating part is… the core experience works beautifully sometimes, and then completely falls apart the next moment.

Our stack right now:

  • STT: Deepgram
  • LLM: Groq using Llama 3.3 70B Versatile
  • TTS: Grok TTS

The issue:

  • Internally, the voice agent often works perfectly.
  • Low latency, smooth responses, natural conversation.
  • But the moment we ask external users to test it, the voice starts cracking, glitching, stuttering, or breaking randomly.
  • Sometimes it works flawlessly for them too… and then suddenly breaks again after a few interactions.

What’s driving us insane is the inconsistency.

We’ve checked:

  • Internet stability
  • Different devices
  • Browsers
  • Concurrency
  • Streaming logic
  • Buffering
  • Latency spikes
  • Sample rate mismatches (at least we think)

But we still cannot pinpoint the root cause.

At this point we genuinely don’t know whether:

  • the issue is in streaming architecture,
  • audio chunk handling,
  • WebRTC,
  • Groq response timing,
  • Deepgram streaming,
  • TTS buffering,
  • or some synchronization issue between all components.

Has anyone here faced similar “works internally but breaks for real users” problems in voice AI systems?

Would love:

  • debugging suggestions,
  • architecture advice,
  • common hidden issues,
  • monitoring ideas,
  • or even theories.

This one issue is literally blocking our launch right now.

reddit.com
u/Electronic_Argument6 — 5 days ago

Our AI Voice Agent Sounds Insane in Demo Calls…. Then Randomly Turns Into a Broken Radio for Real Users

Hey everyone,

We’ve been building a real-time AI voice agent for the last 4 months and we’re finally in the final stages. The frustrating part is… the core experience works beautifully sometimes, and then completely falls apart the next moment.

Our stack right now:

  • STT: Deepgram
  • LLM: Groq using Llama 3.3 70B Versatile
  • TTS: Grok TTS

The issue:

  • Internally, the voice agent often works perfectly.
  • Low latency, smooth responses, natural conversation.
  • But the moment we ask external users to test it, the voice starts cracking, glitching, stuttering, or breaking randomly.
  • Sometimes it works flawlessly for them too… and then suddenly breaks again after a few interactions.

What’s driving us insane is the inconsistency.

We’ve checked:

  • Internet stability
  • Different devices
  • Browsers
  • Concurrency
  • Streaming logic
  • Buffering
  • Latency spikes
  • Sample rate mismatches (at least we think)

But we still cannot pinpoint the root cause.

At this point we genuinely don’t know whether:

  • the issue is in streaming architecture,
  • audio chunk handling,
  • WebRTC,
  • Groq response timing,
  • Deepgram streaming,
  • TTS buffering,
  • or some synchronization issue between all components.

Has anyone here faced similar “works internally but breaks for real users” problems in voice AI systems?

Would love:

  • debugging suggestions,
  • architecture advice,
  • common hidden issues,
  • monitoring ideas,
  • or even theories.

This one issue is literally blocking our launch right now.

reddit.com
u/Electronic_Argument6 — 5 days ago

Our AI Voice Agent Sounds Insane in Demo Calls…. Then Randomly Turns Into a Broken Radio for Real Users

Hey everyone,

We’ve been building a real-time AI voice agent for the last 4 months and we’re finally in the final stages. The frustrating part is… the core experience works beautifully sometimes, and then completely falls apart the next moment.

Our stack right now:

  • STT: Deepgram
  • LLM: Groq using Llama 3.3 70B Versatile
  • TTS: Grok TTS

The issue:

  • Internally, the voice agent often works perfectly.
  • Low latency, smooth responses, natural conversation.
  • But the moment we ask external users to test it, the voice starts cracking, glitching, stuttering, or breaking randomly.
  • Sometimes it works flawlessly for them too… and then suddenly breaks again after a few interactions.

What’s driving us insane is the inconsistency.

We’ve checked:

  • Internet stability
  • Different devices
  • Browsers
  • Concurrency
  • Streaming logic
  • Buffering
  • Latency spikes
  • Sample rate mismatches (at least we think)

But we still cannot pinpoint the root cause.

At this point we genuinely don’t know whether:

  • the issue is in streaming architecture,
  • audio chunk handling,
  • WebRTC,
  • Groq response timing,
  • Deepgram streaming,
  • TTS buffering,
  • or some synchronization issue between all components.

Has anyone here faced similar “works internally but breaks for real users” problems in voice AI systems?

Would love:

  • debugging suggestions,
  • architecture advice,
  • common hidden issues,
  • monitoring ideas,
  • or even theories.

This one issue is literally blocking our launch right now.

reddit.com
u/Electronic_Argument6 — 5 days ago

been obsessed with how profitable micro saas founders find their ideas. not the ones who got lucky with a viral launch. the quiet ones making consistent money that nobody writes about because the product is too boring for a blog post.

talked to 12 of them over the last few months. some through reddit, some through communities, a couple through cold outreach. asked them all the same question: how did you actually find this idea?

none of them said brainstorming. not one.

here's what they actually said.

founder 1 (scheduling tool for trade contractors, $14k/month):

"i was a contractor for 8 years. used to schedule jobs on a whiteboard. tried every scheduling app and they were all built for office meetings. i just needed something that handled multiple crews across multiple job sites with weather delays. built the ugly version in a month. every contractor i showed it to said where do i pay."

the pattern: he WAS the customer. he didn't research the problem. he lived it.

founder 2 (invoice escalation for freelancers, $8k/month):

"saw the same complaint on r/freelance like once a week. someone asking how to chase late payments without being awkward. freshbooks sends a reminder email and that's it. i built a tool that does polite nudge day 3, firm follow up day 7, and a 'my accountant is now handling this' template at day 30. charges $15/month."

the pattern: he found the idea by being active in a community. not lurking. actually reading what people said repeatedly.

founder 3 (menu syncing for restaurants, $11k/month):

"my friend owns a restaurant. complained every week about updating menus across uber eats, doordash, grubhub. 45 minutes per change. i built a tool where you update once and it pushes everywhere. showed it to 5 restaurant owners. 4 signed up the same day."

the pattern: someone close to him had the problem. he didn't go searching for it. he paid attention when someone he knew complained.

founder 4 (review monitoring for small ecommerce, $6k/month):

"i was reading 1 star reviews on a competitor tool for my own store. realized i was doing this manually every week for 3 different marketplaces. built a scraper that pulls all new reviews into one dashboard and alerts me when a negative one drops. started selling it after another seller asked how i caught a bad review so fast."

the pattern: he built it for himself first. the product was his own manual workflow automated.

founder 5 (client portal for accountants, $22k/month):

"accountants use 6 different tools to do what should be one simple thing. collect documents from clients, send reminders for missing stuff, track deadlines. i know because my mom is an accountant and her desk was covered in sticky notes. built a portal where clients upload everything in one place and the accountant sees a dashboard of who's missing what."

the pattern: family member's problem. he saw the chaos firsthand.

the 5 patterns across all 12 founders:

  1. seven of them WERE the customer at some point. they built the tool they personally needed.
  2. three found the idea by being active in niche communities and noticing the same complaint repeated weekly.
  3. two found it through someone close to them. friend, family member, former colleague.
  4. zero found it by brainstorming, googling "saas ideas," or asking chatgpt.
  5. every single one of them could describe the product in two sentences or less. if you need a paragraph to explain what your saas does the problem isn't clear enough.

the uncomfortable takeaway:

The best micro SaaS ideas don’t come from being clever.

They come from paying attention.

Pay attention to your own manual workflows.
Pay attention to what people in communities keep complaining about.
Pay attention when someone you know describes a frustration for the third time.

That’s exactly how I came up with my SaaS idea.

The ideas are everywhere. You’re just scrolling past them.

u/Electronic_Argument6 — 13 days ago
▲ 133 r/StartupMind+3 crossposts

been obsessed with how profitable micro saas founders find their ideas. not the ones who got lucky with a viral launch. the quiet ones making consistent money that nobody writes about because the product is too boring for a blog post.

talked to 12 of them over the last few months. some through reddit, some through communities, a couple through cold outreach. asked them all the same question: how did you actually find this idea?

none of them said brainstorming. not one.

here's what they actually said.

founder 1 (scheduling tool for trade contractors, $14k/month):

"i was a contractor for 8 years. used to schedule jobs on a whiteboard. tried every scheduling app and they were all built for office meetings. i just needed something that handled multiple crews across multiple job sites with weather delays. built the ugly version in a month. every contractor i showed it to said where do i pay."

the pattern: he WAS the customer. he didn't research the problem. he lived it.

founder 2 (invoice escalation for freelancers, $8k/month):

"saw the same complaint on r/freelance like once a week. someone asking how to chase late payments without being awkward. freshbooks sends a reminder email and that's it. i built a tool that does polite nudge day 3, firm follow up day 7, and a 'my accountant is now handling this' template at day 30. charges $15/month."

the pattern: he found the idea by being active in a community. not lurking. actually reading what people said repeatedly.

founder 3 (menu syncing for restaurants, $11k/month):

"my friend owns a restaurant. complained every week about updating menus across uber eats, doordash, grubhub. 45 minutes per change. i built a tool where you update once and it pushes everywhere. showed it to 5 restaurant owners. 4 signed up the same day."

the pattern: someone close to him had the problem. he didn't go searching for it. he paid attention when someone he knew complained.

founder 4 (review monitoring for small ecommerce, $6k/month):

"i was reading 1 star reviews on a competitor tool for my own store. realized i was doing this manually every week for 3 different marketplaces. built a scraper that pulls all new reviews into one dashboard and alerts me when a negative one drops. started selling it after another seller asked how i caught a bad review so fast."

the pattern: he built it for himself first. the product was his own manual workflow automated.

founder 5 (client portal for accountants, $22k/month):

"accountants use 6 different tools to do what should be one simple thing. collect documents from clients, send reminders for missing stuff, track deadlines. i know because my mom is an accountant and her desk was covered in sticky notes. built a portal where clients upload everything in one place and the accountant sees a dashboard of who's missing what."

the pattern: family member's problem. he saw the chaos firsthand.

the 5 patterns across all 12 founders:

  1. seven of them WERE the customer at some point. they built the tool they personally needed.
  2. three found the idea by being active in niche communities and noticing the same complaint repeated weekly.
  3. two found it through someone close to them. friend, family member, former colleague.
  4. zero found it by brainstorming, googling "saas ideas," or asking chatgpt.
  5. every single one of them could describe the product in two sentences or less. if you need a paragraph to explain what your saas does the problem isn't clear enough.

the uncomfortable takeaway:

The best micro SaaS ideas don’t come from being clever.

They come from paying attention.

Pay attention to your own manual workflows.
Pay attention to what people in communities keep complaining about.
Pay attention when someone you know describes a frustration for the third time.

That’s exactly how I came up with my SaaS idea.

The ideas are everywhere. You’re just scrolling past them.

u/Electronic_Argument6 — 6 days ago
▲ 0 r/sidehustle+1 crossposts

Most people sell websites the hard way. They message businesses, say the site needs work, try to book a call, send examples, then hope the owner is interested enough to keep talking.

What works better for me is way simpler. I call local businesses and tell them I already made a better version of their website and ask if they want a quick demo. That gets way more attention because now it is not some vague pitch, it is something real. They can either ignore it or get curious enough to look.

If they are interested, I spend the next couple days building a cleaner version of what they already have. Better layout, better mobile, clearer headline, stronger trust, better call to action, just something that looks more current and makes the business look legit. Then I show it on the call.

That changes the whole sales process because I am not trying to convince them with words anymore. They can actually see it, click through it, compare it to what they have now, and instantly get the difference.

The other big part is pricing. Most people still try to hit local businesses with some big upfront invoice, but that creates a lot of resistance. I usually do monthly instead, around $90 to $120 depending on the business. That usually includes the website, support, updates, and a few extras. Way easier for a small business owner to say yes to than a random multi-thousand-dollar bill.

And once it is live, they usually stay, because now the site is tied into how they operate. Leads come through it, updates go through you, their online presence depends on it. So you are not just the guy who sold a website once, you become part of the business every month.

That is why I like this model.

The demo gets attention, the monthly pricing gets the yes.

Happy to answer questions if anyone wants to know how I do it.

•https://lovable.dev → good for quickly building sites, you connect everything yourself (forms, bookings, etc)

•https://bolt.new → similar idea, fast builds, more manual setup after

•https://agenzy.app → all-in-one (site, crm, automations, bookings), easier once you have multiple clients or want to upsell too

•claude → for ideas, structure, and improving copy

•canva → to quickly brainstorm layouts / visuals 
u/Electronic_Argument6 — 14 days ago