Bolna's Agent Studio lets any business build and deploy a production-grade voice AI agent in minutes, no prompt engineering. Upload a doc or answer a few guided questions, and Studio assembles a call-ready agent from production-tested modules. Sign up and start calling on Day 0.
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!
Everyone ends up building similar-sounding voice agents if they're using the same templates. How do you keep each one feeling unique?
The auto-assemble-from-a-doc part is the real leap here, and it's also where I'd look hardest. When we generated agent flows from source material, the thing that never came for free was the negative space: a caller asks something the doc just doesn't cover, and the model improvises a confident policy answer instead of saying 'I don't know, let me transfer.' Does Studio insert those refusal and escalation boundaries automatically, or is that still the part you tune by hand after the agent is generated?
A real-time analytics dashboard showing live sentiment and call drop-off rates during campaigns would help teams tweak prompts on the fly. Right now we mostly wait until after to see what worked.
Spent a few minutes poking around and the multilingual demos actually handled code-switching better than I expected. Pricing transparency was a nice surprise too, most voice AI vendors make you book a call just to see numbers.
Would love to see a built-in call quality analytics dashboard that breaks down latency, transcription accuracy, and drop-off points per language. Right now we're piecing it together from logs and it makes it hard to spot where the model is struggling in Hindi versus English versus Tamil. A single view that surfaces the metrics that matter most would save our team hours every week and help us fine-tune without guesswork.
A dashboard view showing live call metrics with filters by region, language, and intent would be super helpful when running thousands of concurrent calls. Right now I'm guessing it's hard to spot issues at scale without granular real-time visibility into performance breakdowns.
Would love to see a built-in call quality analytics dashboard showing latency, transcription accuracy, and drop-off rates per language. Right now it's hard to benchmark performance across different regional deployments without piecing together data from multiple sources.
Finally got around to testing Bolna for an outbound campaign and was honestly surprised how natural the voice sounded in Hindi and Tamil. Setup took maybe an afternoon.
Finally moving away from long iterations because chatgpt just doesn't understand how my voice agent is supposed to work! Glad to know it is trained on real data.
Most of the thread is on edge cases and compliance. The linguistic complexity claim is the one I'd poke at, we run voice on the support side in a lot of languages.
On real calls people don't stay in one language. They switch mid sentence, and the worst place is digits. Someone speaking English will still say an order number or a postcode in their own language, almost every time. Same when they get annoyed, then a whole sentence flips.
If language is picked at call start and pinned there, that is where transcription falls apart, and it falls apart on the field you least want wrong.
So does the agent detect the switch inside the call and follow it, or is it locked once the call starts? And are digits handled separately from the rest..
Honestly the multilingual support surprised me most, our test calls in Hindi and Spanish both sounded pretty natural compared to other voice AI tools I've tried. Setup was straightforward too.
The async setup was surprisingly painless for handling multilingual flows, and the latency on outbound calls felt close to real human pacing.
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?
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.
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
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?
Finally moving away from Claude projects which draft emojis in the prompt to contextualised agent which works :)
Voice AI usually means wiring together ASR, LLM, and TTS yourself before you've even built the actual conversation. Studio hides all that; you describe the call and it's live.Best part is watching non-technical folks like ops, marketing ship a working agent
About Bolna Agent Studio on Product Hunt
“Build Voice AI Agent in 10 Minutes”
Bolna Agent Studio launched on Product Hunt on July 21st, 2026 and earned 138 upvotes and 34 comments, placing #11 on the daily leaderboard. Bolna's Agent Studio lets any business build and deploy a production-grade voice AI agent in minutes, no prompt engineering. Upload a doc or answer a few guided questions, and Studio assembles a call-ready agent from production-tested modules. Sign up and start calling on Day 0.
Bolna Agent Studio was featured in SaaS (43.2k followers), Artificial Intelligence (474.1k followers) and No-Code (5.8k followers) on Product Hunt. Together, these topics include over 163.3k products, making this a competitive space to launch in.
Who hunted Bolna Agent Studio?
Bolna Agent Studio was hunted by Kevin William David. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Bolna Agent Studio stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Kevin William David
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!