Build, Buy, or Wait? Voice AI for the Enterprise
Voice agents are going into production everywhere now: customer support, sales calls, collections, hiring, appointment booking.
But the engineering reality behind a smooth voice demo is messier than anyone talks about publicly.
Awkward pauses that make callers hang up. Speech-to-text, LLM and text-to-speech all fighting for the same GPU budget. Cost per minute that looks fine in a pilot and breaks the business case at enterprise call volume. Models that stumble on Indian languages, accents and mid-sentence code-switching.
And every CTO is stuck on the same question: do we build the stack in-house, buy a platform, or wait for the models to mature?
Most teams are answering that in isolation, through pilots, rewrites, and trial and error.
This live session changes that.
Join us for a live CTO-to-CTO conversation between the teams running both layers of the voice stack in production: the agent and the GPU underneath it. No slide decks. No vendor pitches. Just an honest, practitioner-level conversation about what’s actually working, and what isn’t.
What we’ll cover:
The build vs. buy decision: what you actually own, and what you’re signing up to maintain
Where latency hides in a voice turn, and the milliseconds that decide whether a caller stays
Cost per minute at scale: what changes between a 100-call pilot and a million-minute month
Indian languages, accents and code-switching: what breaks first, and how teams are fixing it
When to wait: which parts of the voice stack are still moving too fast to lock in
Speakers:
Devansh Ghatak, CTO, Simplismart, who leads the inference platform serving ASR, LLM and TTS models for voice AI teams
Prateek Sachan, CTO, Bolna, who leads the orchestration platform used to build and deploy voice agents over the phone