- SuperBryn AI: Orchestrating Voices
- Posts
- 5 Seconds to Save a Sale: How AI Callbacks Rescue 75% of Dead Leads
5 Seconds to Save a Sale: How AI Callbacks Rescue 75% of Dead Leads
Imagine this: You fill out a form for a product or service, and within seconds, you get a call—not from an IVR, not from a bot that repeats “Press 1 for sales”—but from a Voice AI Agent that actually understands you.
Nikkitha Shanker
April 03, 2025
📞 Today’s Demo: AI-Powered Instant Callbacks
We’re bringing this to life with a real healthcare use case. You fill out a form on MyHealth, a healthcare aggregator. The moment you hit submit…
That’s one step closer to replacing rigid IVRs with something truly conversational.
💡 Why This Matters: BEYOND HEALTHCARE
Slow Follow-Ups = Lost Revenue
Here’s the hard truth: 75% of leads go cold if they’re not contacted within five minutes.
Yet, most businesses take hours (or even days) to follow up. The result? Lower conversion rates, frustrated customers, and lost revenue.
What if…
🔹 A car dealership followed up in seconds—before a lead looked elsewhere?
🔹 An e-commerce store called with smart recommendations—reducing returns?
🔹 A bank guided users through loan applications—without frustrating delays?
🔹 A logistics company updated customers proactively—cutting support tickets?
Can you think of industries or use cases where things could be simpler for you or your customers? Reach out to us!
🔍 STT Model Selection: Not a One-Time Choice, But a Continuous Process
Speech-to-Text models aren’t “set & forget.” Industry needs evolve, models update, and real-world performance shifts. Continuous monitoring of accuracy, speed, & cost ensures you’re always using the best model for your use case—because yesterday’s top performer might not be today’s best fit. 🚀
🔊 Voice-to-Voice Models: The Black Box Challenge
Voice-to-voice AI models are buzzing with potential, but their “black box” nature 🎩 —where decision-making remains a mystery—raises serious concerns. Understanding how these models reach conclusions is critical, especially in high-stakes industries like healthcare and finance, where a single error could have huge consequences ⚠️
To build trustworthy AI, we need more transparency 🔍 and control 🎛️ over these systems. Can we make AI explain itself? That’s the challenge ahead.
Some Context about SuperBryn 📌
We’re Nikkitha & Neethu. We built voice apps for Indian hospitals—only to realize existing Voice AI didn’t work. It failed on accents, struggled in real-world conditions, and was rigid & expensive. So, we are building SuperBryn—a Voice AI Orchestration Layer that adapts dynamically, making AI truly work for diverse markets like India. |
🔮 WHAT'S COMING NEXT
Last week, we let users test Tara directly—and the feedback was invaluable. Here’s what’s coming next: