Bolna Agent Studio - Build Voice AI Agent in 10 Minutes

Hey Product Hunt 👋

We are the team behind Bolna, and we are here to make the whole process of building a Voice AI agent a whole lot easier and quicker than ever before.

Let’s be honest! The starting point to build a Voice AI agent has always been intimidating. Hours of effort gathering context, foolproof guardrails, detailed conversation flows, and yet something sifts through the whole orchestration, leading the agent to embarrassingly fail at deployment.

Agent Studio on Bolna takes all the above hindrances away between you and your perfect Voice AI agent by specifically putting every piece of the matrix together with one drag-and-drop brief. All you have to do is upload a contextual document and let it fill in the blanks to deliver a production-grade voice agent which can go live the same day as you sign up.

What makes Agent Studio handy for Voice AI agents:

• No prompt engineering expertise to get started.

• A modular structure in place including Identity, Conversation and Closing blocks.

• Built on thousands of proven templates applied across sectors.

• Handles all edge cases, instead of just linear scripts.

• Auto-picks the best combination of models for each use case.

• Warm endings and fallbacks for smooth user experiences.

• Reviews every agent across quality benchmarks and fills in whatever is missing before shipping the agent.

This changes the way Voice AI agents were fundamentally built, taking weeks to curate the perfect prompt and deployment. Agent Studio makes your perfect Voice AI agent come to life with a single session, delivering a production-grade deployment that holds up through real calls for enterprise scale. The barrier to building and scaling with voice has now dropped to almost nothing.

Presenting this to the Product Hunt community is huge for us, with weeks of deliberation gone into each step of the process. We’d love for you to give Agent Studio a shot to build Voice AI agents. Go all out with your use cases on Agent Studio, and we are sure you’d adopt it as your core Voice AI stack! And if you end up loving it as much as our beta users have, we’d love your support here!

Every upvote and comment means a lot to the team.

So what's your excuse for not building a Voice AI Agent anymore?

Cheers,

Sonam from Bolna

P.S. We'll be around to answer questions throughout the day, so shoot all your questions right away!

Hey Product Hunt 👋

For the longest time, building a Voice AI agent at Bolna meant one of us sitting down and building it by hand.

I have spent tens of hours building agents, any my team, who is building agents for some of India's largest enterprises, has probably spent 100x that.

Every new agent meant hours of gathering context, writing guardrails, mapping conversation flows, and second-guessing every edge case. We "Did Things that Didn't Scale" until we just physically couldn't. There was too much of a gap between the quality and speed of agent building required and what we could provide (even as our FDE team grew from 2 to 20 in 3 months)

Then somewhere past 200K+ hours of calls, a pattern emerged. The same building blocks. The same edge cases. The same fixes we kept making by hand, over and over.

Agent Studio is us finally putting all of that back into the product itself.

You upload a context document. Drag and drop a brief. And it -

1. Fills in the blanks using thousands of patterns proven across sectors

2. Structures the agent into Identity, Conversation and Closing blocks

3. Auto-picks the best combination of models for your use case

4. Handles edge cases, warm endings and fallbacks, not just linear scripts

5. Reviews itself against quality benchmarks and fills whatever's missing before shipping

Sign up in the morning, have a production-grade agent taking real calls by evening. No more prompting frustratiosn.

The part I keep coming back to - the hardest thing about Bolna's first two years was the manual work. Agent Studio is us handing that exact superpower to anyone who signs up.

The barrier to building with Voice has dropped to almost nothing.

We'd love for you to break it, push it, throw your weirdest use case at it. Give us your thoughts!

Super proud of @xan_ps and the entire team for building and shipping this!

So - what's stopping you from shipping a Voice AI agent today?

Back on PH after a long time and there's a reason! While building out voice agents I was always looking for ways I could vibe-create an agent and just talk to it. While Claude solved for building apps for custom use cases by just explaining in English, I found an equivalent for the Voice AI sector here!

Loving it through and through! But have a few suggestions. How can I share those, team?

insane !!!

it made life easier to write agents on the platform itself , now i can easily make agents for different usecases from different industries with Agent Studio within just 5 mins of uploading few documents and context

Looks super easy to use! Congratulations on the launch.

Maitreya, the 200K hours of calls turning into reusable blocks is the most convincing part of this story: that is the kind of pattern library a hand-built agent never benefits from.

My question comes from my corner of the market. I build AI for healthcare, and voice is the obvious next interface for appointment reminders and patient intake, but every call recording there contains protected health information.

Do you support healthcare use cases today: things like a BAA, redaction of recordings, or region-locked storage? That answer decides whether teams like mine can even prototype on Bolna.

the "handles all edge cases, not just linear scripts" line is the part I'd want to poke at before pointing real call volume at it. since Studio can get you live the same day you sign up, is there a staging/sandbox step where you can run a batch of adversarial or unusual calls against the generated agent before it starts taking live traffic, or is the expectation that you go live and iterate on real calls from day one?

The async setup was surprisingly painless for handling multilingual flows, and the latency on outbound calls felt close to real human pacing.