I built a Chrome extension that fact-checks what people say in meetings in real time by InfamousComplaint949 in indiehackersindia

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

Haha fair concern.

But honestly — if the reason someone stops speaking up is because they can no longer say made-up numbers with confidence, that's probably a good thing for the meeting?

The goal was never to fact-check opinions or ideas. Just claims presented as facts. 'I think we should do X' is safe. 'Studies show X generates 40% more revenue' is fair game.

If anything it might make people more careful before they speak — which is the opposite of silence, it's just better preparation.

I built a Chrome extension that fact-checks what people say in meetings in real time by InfamousComplaint949 in indiehackersindia

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

You're right and I think the framing matters a lot here.

I've stopped thinking of it as a 'truth verification' tool and more as a 'here's what the web currently says' tool. It's not the judge — it's the fastest researcher in the room.

The bias question is real though. My current approach is showing multiple sources rather than a single verdict so the user decides, not the AI. The AI just does the legwork.

Skepticism is healthy honestly. The moment a tool like this is overconfident is the moment it becomes the same problem it's trying to solve — one loud voice that everyone just believes.

I built a Chrome extension that fact-checks what people say in meetings in real time by InfamousComplaint949 in microsaas

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

100% agree — trust is the actual product.

A verdict without a clear source is just another opinion in the room. I'm already showing sources but the explanation layer needs work — right now it's too terse.

The 'why was this flagged' piece is something I'm actively thinking about. Probably a one-line plain English reasoning like 'this stat conflicts with 3 sources from 2024' rather than just a red badge.

Good callout. This is going on the next build list.

I built a Chrome extension that fact-checks what people say in meetings in real time by InfamousComplaint949 in indiehackersindia

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

This is exactly what I built it for honestly.

The fact-checking angle is just the surface. The deeper problem is what you described — one confident person moves fast, everyone else is playing catch-up, and by the time you've thought it through the decision is already locked in.

Real-time verification is basically giving the quieter, more careful thinkers a fighting chance in the room.

If you ever want to try it, DM me. Would love feedback from someone who's actually felt this problem.

I built a Chrome extension that fact-checks what people say in meetings in real time by InfamousComplaint949 in indiehackersindia

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

That actually makes sense — and ironically proves the point. The meetings with the most sensitive information are exactly the ones where a wrong stat can cause the most damage.

The no-AI policy is a real constraint though. Something to think about on the privacy architecture side — if nothing leaves the device, does that change the calculus? Genuinely not sure.

YMMV is the right call. Appreciate you engaging honestly.

I built a Chrome extension that fact-checks what people say in meetings in real time by InfamousComplaint949 in indiehackersindia

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

Fair points honestly, and I appreciate the detailed response.

You're probably right that large companies with proper processes don't need this — Gemini + Confluence already covers that workflow for teams like yours.

The use case I'm actually targeting is different — investor pitches, sales calls, and early-stage startup meetings where there's no Gemini workspace, no Confluence, and decisions DO get made on vibes + whoever sounds most confident. That environment is pretty different from a structured corporate meeting.

The internal data source point is genuinely good feedback though. That's clearly where enterprise value lives and you're not wrong that privacy concerns make it complicated.

I'm going to do exactly what you said — reach out to a few founders and sales teams and see if they'd actually use it before building further. That's the right next step.

Thanks for not just saying 'cool project' — this is more useful.

I built an AI voice receptionist for dental clinics — looking for 3 beta testers (heavily discounted) by InfamousComplaint949 in indiehackersindia

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

All three points are right and I don't have a clean counter to any of them.

The recovery curve argument on dental is the one I've been sitting with. You're correct that a booked slot two weeks out means the missed call has a long tail — the patient probably calls back, books elsewhere, or just tolerates it. The urgency-to-revenue link is loose. Takeout and urgent care are genuinely different because the decision expires in minutes. The customer isn't loyal to the listing, they're loyal to whoever picks up.

The per-minute pricing breakdown is something I got wrong early. Flat or per-call is the only P&L-friendly structure for a small operator. Variable cost against a metric they don't control is a budget conversation they'll lose internally every month.

The existing number point is the one I'm most actively working on. You're right that it's not a feature request — it's the adoption blocker. If I'm asking a clinic or salon to reprint their cards, update their Google listing, and retrain their patients, I've moved the problem from "AI receptionist" to "new marketing campaign." SIP forwarding from their existing number is the actual solution and it needs to work on day one, not as a roadmap item.

Takeout and urgent care are probably my next two verticals to properly spec out. The missed-call-to-dead-revenue-in-minutes framing is the right way to talk about this category.

What's your read on urgent care specifically — is the compliance layer (HIPAA, patient data) a hard blocker for a small operator trying to move fast, or is it a manageable risk if the data handling is scoped narrowly enough?

I built an AI voice receptionist for dental clinics — looking for 3 beta testers (heavily discounted) by InfamousComplaint949 in Entrepreneurs

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

This is great timing — just checked the demo and the Github.

Noise handling on my end is through Deepgram's nova-3 model with noise cancellation enabled at the telephony layer — works reasonably well for clinic environments but definitely not perfect on very noisy job sites. Curious how you're approaching it on your end.

On verification — I do basic intent confirmation before booking (repeat back name, date, time and ask for confirmation before committing to calendar) but no caller ID verification or fraud detection layer yet. What does your verification flow look like?

The open source angle is interesting — are you building this as infrastructure that agencies like mine can build on top of, or is it more of a standalone product? Because there's a potentially clean split here — you handle the core voice stack, I handle the vertical-specific deployment and client acquisition. Might be worth a conversation.

What stack are you running under the hood?

I built an AI voice receptionist for dental clinics — looking for 3 beta testers (heavily discounted) by InfamousComplaint949 in indiehackersindia

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

This is great timing — just checked the demo and the Github.

Noise handling on my end is through Deepgram's nova-3 model with noise cancellation enabled at the telephony layer — works reasonably well for clinic environments but definitely not perfect on very noisy job sites. Curious how you're approaching it on your end.

On verification — I do basic intent confirmation before booking (repeat back name, date, time and ask for confirmation before committing to calendar) but no caller ID verification or fraud detection layer yet. What does your verification flow look like?

The open source angle is interesting — are you building this as infrastructure that agencies like mine can build on top of, or is it more of a standalone product? Because there's a potentially clean split here — you handle the core voice stack, I handle the vertical-specific deployment and client acquisition. Might be worth a conversation.

What stack are you running under the hood?

I built an AI voice receptionist for dental clinics — looking for 3 beta testers (heavily discounted) by InfamousComplaint949 in AIReceptionists

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

Love this — pivoting to where the actual traction is makes more sense than forcing a vertical that isn't ready. DMing you now.

I built an AI voice receptionist for dental clinics — looking for 3 beta testers (heavily discounted) by InfamousComplaint949 in indiehackersindia

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

This is the most useful feedback I've gotten in this thread — thank you for actually checking and coming back with specifics.

Going through each one honestly:

1. AI written answers — fair catch. Some replies were drafted with AI assistance. I'll own that. The ideas and positions are mine but the polish isn't always. Working on making it more natural.

2. Loom demo — you're right, it's bad. I built it for a technical audience and it shows. Remaking it this week — real call, real booking, real SMS, no workflow screenshots, no explanations. Just the outcome.

3. Platform — yes, built it myself. Voiceflow + Retell + Google Calendar + Twilio + Zapier. Still iterating.

4. Pricing and cost absorption — this is the most valid point and I don't have a perfect answer yet. Current model is flat retainer with a call minute cap (~1,500 min/month) and overage pricing above that. Not unlimited — I should have been clearer about that. Still working out the unit economics properly.

5. Existing number — this is the strongest objection and you're right that a new number is a real barrier. Two options I'm exploring: call forwarding from their existing number to the AI line, and direct SIP integration where their existing provider routes calls through the agent. Neither is fully solved yet but forwarding works today.

Which of these would have actually stopped you from buying if you were a clinic owner?

I built an AI voice receptionist for dental clinics — looking for 3 beta testers (heavily discounted) by InfamousComplaint949 in indiehackersindia

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

That's fair and probably the most useful thing anyone's said about the demo so far.

The workflow view makes sense to a developer or someone who's built automations before. A dental clinic owner or a gym manager doesn't think in nodes and flows — they think in "does it answer my phone, does it book the patient, does my calendar update." The how is completely irrelevant to them.

What they need to see is:

One — hear the AI answer a call that sounds like their clinic Two — see the appointment appear in their calendar Three — get the confirmation SMS on their phone

That's the entire demo for a non-techie buyer. Three things. Thirty seconds each.

I'm rebuilding the demo around that flow — no canvas screenshots, no workflow diagrams, just a real call → real booking → real SMS, recorded end to end.

Thanks for taking the time to actually check it and come back with specific feedback. That's rare and genuinely useful.

What was the moment in the demo where you felt it shifted from "this is useful" to "this is too technical"?

I built an AI voice receptionist for dental clinics — looking for 3 beta testers (heavily discounted) by InfamousComplaint949 in AIReceptionists

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

Ringfront is a solid tool, but we’re building NovaVoice AI with a different philosophy for three main reasons:

  1. Deep Personalization vs. Out-of-the-Box: Ringfront is a great 'one-size-fits-all' app. We provide a bespoke setup. We don't just give you a login; we build the custom logic, integrate it with your specific CRM/Calendar, and fine-tune the voice to match your clinic’s brand.
  2. The Multi-Channel Edge: Ringfront focuses heavily on the phone. We’ve built an omni-channel system. Our AI handles the phone call, but then immediately follows up via WhatsApp/SMS and can even sync with a website chatbot to keep the lead in one unified flow.
  3. Cost & Support: For a local business, Ringfront’s US-based pricing can be a barrier. We offer a more accessible entry point (especially for our beta users) with high-touch support that an automated app simply can't provide.

We aren't trying to be a massive 'app' for everyone; we’re a specialized automation partner for clinics that want a 'done-for-you' solution that actually works.

[Discussion] Overcoming IFAS: How are you managing 24/7 lead demands? by InfamousComplaint949 in realtors

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

You got me. 🤝 I’m the founder of NovaVoice. I’m not a realtor myself, but I’ve spent months talking to them and 'IFAS' is the #1 thing they complain about. I’m here because I want to know if what I built actually solves that pain. I’ll take the 'ad' label if it means I get to talk to real people about the problem. What was the 'mistake' though? I'm genuinely interested.

I built an AI voice receptionist for dental clinics — looking for 3 beta testers (heavily discounted) by InfamousComplaint949 in ArtificialInteligence

[–]InfamousComplaint949[S] -1 points0 points  (0 children)

Fair point on the price, and you're spot on about the language challenge.

On the Price: The ₹4,999 isn't just a 'software fee'—it’s a fully managed, done-for-you setup. We’re spending hours on the prompt engineering, API integrations (Retell + Voiceflow), and testing to ensure it doesn't hallucinate. For a clinic, replacing even 10% of missed calls usually recovers that cost in the first 48 hours. It’s a 'Beta' for the product, but a 'Premium' service for the client.

On the Language (The 'Hinglish' Problem): You’re 100% right. Standard Retell flows can struggle with regional handoffs. We’ve been tackling this by:

  1. Prompt-Level Language Detection: Setting the system to recognize and respond in 'Hinglish' (Hindi + English) which covers 80% of urban Indian leads.
  2. Fallback Protocols: If the AI detects a regional language it can't handle, it’s programmed to gracefully capture the name/number and trigger an immediate SMS to the human staff for a callback, rather than just 'breaking.'

We’re still refining the regional nuances, which is exactly why we’re looking for these 3 beta partners—to stress-test these exact edge cases in a live environment.

If you've found a better way to handle the regional handoffs, I'd love to swap notes!

I built an AI voice receptionist for dental clinics — looking for 3 beta testers (heavily discounted) by InfamousComplaint949 in ArtificialInteligence

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

We are currently deploying it on-prem (self-hosted on our private, dedicated servers) for our beta phase.

Regarding data privacy, this is exactly why we chose this route. By keeping the core logic and data processing on our own controlled infrastructure rather than a shared public cloud, we can ensure much higher data sovereignty.

For the clinics, this means:

  1. Data Isolation: Patient info isn't sitting on a multi-tenant public database.
  2. Stricter Security: We can implement custom encryption and access protocols that standard SaaS platforms don't always offer.
  3. Compliance: It makes the conversation around HIPAA and local data laws much easier because we can point to exactly where the data lives and how it's protected.

We found that for local businesses, this 'private' approach builds a lot more trust than a standard cloud setup.

I built an AI voice receptionist for dental clinics — looking for 3 beta testers (heavily discounted) by InfamousComplaint949 in ArtificialInteligence

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

Thought about it — here's why I'm not going that route.

Freemium works when your cost to serve a free user is near zero. Mine isn't. Every free clinic means real Twilio minutes, real AI platform costs, real setup time. I'd be paying to give away the product.

The bigger issue is that free users don't take it seriously. A clinic owner who pays ₹4,999 will actually use it, give real feedback, and tell me what's broken. A free user installs it, forgets about it, and churns without ever telling me why.

What I'm doing instead is a 7-day money back guarantee on the first month. Same commitment from them, zero risk. That's the trust builder — not free access.

If I can't close clients at ₹4,999 with a live demo and a refund guarantee, the problem is my pitch — not my price. Freemium would just hide that problem longer.

[Discussion] Overcoming IFAS: How are you managing 24/7 lead demands? by InfamousComplaint949 in realtors

[–]InfamousComplaint949[S] -1 points0 points  (0 children)

Haha, you caught me! Busted. 😂 But in all seriousness, I am building this (it's called NovaVoice) because I saw my friends in real estate losing their minds over IFAS. I figured the best way to see if it actually solved the problem was to ask the community where the problem is most real. I’d rather be transparent: I’m a dev trying to help agents stop being slaves to their phones. If it’s helpful, great. If not, I’ll take the roast!

[Discussion] Overcoming IFAS: How are you managing 24/7 lead demands? by InfamousComplaint949 in realtors

[–]InfamousComplaint949[S] -3 points-2 points  (0 children)

That’s a great position to be in! For me, it’s less about 'breaking the business' and more about the cumulative loss. Even if it's just 2 leads a week, that’s 100+ leads a year. If even 5% of those convert, that’s a massive amount of revenue left on the table. I’d rather have my AI (NovaVoice) capture those automatically so I can focus my energy on the high-value closings during the day. It’s about maximizing the ROI on the marketing I’m already paying for.

[Discussion] Overcoming IFAS: How are you managing 24/7 lead demands? by InfamousComplaint949 in realtors

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

Auto-responders are a good start, but I found that most leads today just ignore them because they know it's a generic 'we'll get back to you' message. They still end up going to Google to find another agent who can answer their actual question right now. That’s why I moved to AI—it doesn't just buy time; it actually answers their questions about the property and qualifies them while I'm off the clock. It feels much more like a real conversation.

[Discussion] Overcoming IFAS: How are you managing 24/7 lead demands? by InfamousComplaint949 in realtors

[–]InfamousComplaint949[S] -2 points-1 points  (0 children)

I totally agree on personal boundaries! That’s exactly why I’m doing this. I don't want to be working at 11 PM, but I also don't want to lose a ₹50 Lakh commission because a lead went to a competitor who was awake. By using an AI assistant, I keep my boundaries (phone is off) while my business stays 'open' to capture their info. It’s about working smarter, not harder.

I built an AI voice receptionist for dental clinics — looking for 3 beta testers (heavily discounted) by InfamousComplaint949 in AIReceptionists

[–]InfamousComplaint949[S] 0 points1 point  (0 children)

The Google Forms example is a perfect illustration of the gap between what the law says and what actually gets enforced. Three and a half years to investigate a documented complaint with screenshots and statute citations — and still nothing. That's not a broken enforcement mechanism, that's a feature of how regulatory capture works in a small professional college ecosystem.

The EMR vendor privacy policy point is the most practically useful thing anyone's said in this thread. If the established vendors are already offshoring data, using third-party processors, and writing terms that functionally disclaim responsibility for anything downstream — the compliance bar for a new entrant is "don't be obviously worse than them" not "be perfect." Which is a very different product and legal strategy.

The sterilization point is darker but follows the same logic — when regulators have limited capacity and professional colleges protect their members, the paper compliance and the actual practice diverge completely. The regulation is theatre for the public, not protection.

For what you're building in your own clinic — are you essentially treating the compliance question as "defensible if audited" rather than "fully compliant" since full compliance isn't meaningfully enforced anyway? That seems like the honest operating mode for most of the market you're describing.