Neethu Mariam Joy

Not every caller is human. 🤖 We built "Gatekeeper "— a client-side fraud & bot detection library for outbound voice AI. Zero deps. Negligible latency. Open source. Check out at github.com/superbryndev/g… @SuperBryn_AI @nikkithashanker

Same call, same question, different answers? That’s LLM nondeterminism. For voice AI, that’s bad news for reliability, debugging, and compliance. @SuperBryn_AI @nikkithashanker @miramurati

Mysteries belong in novels, not conversations. @SuperBryn_AI @nikkithashanker

Launched your voice agent in prod? Congrats!!!! Now you’re flying blind. 🚀🕶️ @SuperBryn_AI @nikkithashanker

Voice agents fail 🙄. @SuperBryn_AI makes fixing them effortless 😎

Launching a Voice AI: 5 minutes. 😎 Keeping it alive in production: 5 existential crises.🤯

Picking the right STT model = tasting 6,000 coffees ☕ ❌ Some are bitter (bad at accents) ❌ Some take forever (slow response) ❌ Some cost $50 a cup (expensive) 🚀 Automate it: ✅ Fetch all models ✅ Test with real calls ✅ Rank top 5 automatically Let the best STT models win

📞 Voice AI = A First Date? Awkward convo? You’re out in 30 secs—just like failed AI calls! 🔹 Short calls (34s) = 🚪 Bye 🔹 Longer chats (1m 32s) = 🗣️ Success Make AI feel natural, and users stay. Had a "bad date" with voice AI? 👇

🚀 Can AI teach itself to talk? Instead of writing endless prompts, what if AI just listened to past calls and figured it out? With reinforcement learning, it starts clueless 🙃, learns from mistakes, and improves with every convo—no babysitting required.

Speaking is expensive, listening is cheap, and thinking is in between. Choose wisely! 💸 ....and I am talking about Voice AI agents here?

Most voice AI assistants today: 🗣 Speech-to-Text → 🧠 LLM → 🔊 Text-to-Speech But this kills emotion & natural flow. The future? Speech-to-Speech AI! 🚀 Will S2S AI replace traditional voice assistants? 🤔

"Just use ChatGPT" is a terrible advice. 🙅‍♀️ It's like using just one app on your phone 📱 Imagine if your phone only had one app. No maps, no messaging, no camera—just one app for everything. Sounds ridiculous, right? 😵‍💫 That’s what sticking to a single AI model is like.

Voice AI without orchestration is like a chaotic karaoke 🎤—everyone’s off-key. With orchestration as the maestro 🤵‍♀️, speech-to-text, LLMs & text-to-speech hit the perfect symphony! 💯 @Vapi_AI @retellai @SynthflowAI @usebland @elevenlabs

AI Agent or Agentic AI ... which one are you building? Imagine using a voice assistant: An AI agent just repeat what you say—ask “What’s the weather?” and they reply “Sunny, 75°F.” But agentic AI? That’s your clever friend who adds, “Hey, might rain later—grab an umbrella!”

Imagine your voice AI as a party guest: MVP is the friend who shows up, greets you right, and keeps the convo flowing. As a voice AI startup, focus on perfecting core command recognition and delivering clear responses first—then build on user feedback to keep the party going.

Voice tech is sprinting ahead 💨 — even if it sometimes sounds like it's still catching its breath 🙄 . A cheeky “Hold that thought!” pre-response can mask the latency of a fully crafted answer. And building a robust STT → LLM → TTS pipeline is a blast to engineer. 💥