India's pioneering agentic AI company. Headquartered in Indore, we build autonomous AI agents, voice systems, domain LLMs, and automation workflows that actually ship.
Framer AI AgentsDesign and publish professional sites with AI
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Hi everyone! 👋
We're excited to launch **Studioform**.
Studioform was born from a simple observation: while AI models have become incredibly capable, many businesses still struggle to turn them into reliable, production-ready products. There are countless demos, but far fewer systems that are scalable, maintainable, and genuinely useful.
Our goal is to bridge that gap by helping startups and businesses build AI-powered applications, automation workflows, and modern web products with a strong engineering foundation.
We're also committed to contributing back to the developer community through open-source projects, technical write-ups, architecture guides, and practical resources that help others build better software.
This launch is just the beginning. We're actively building new tools, experimenting with AI workflows, and sharing what we learn along the way.
We'd love your feedback:
* What AI workflows or developer tools would you like to see next?
* What challenges are you facing when building with AI today?
* What features or services would make Studioform more valuable to you?
Thank you for checking us out—we're looking forward to the discussion and appreciate every piece of feedback. 🚀
Report
Spent a few minutes playing with their voice agent and the latency felt surprisingly snappy for a domestic build. Curious how their domain LLMs hold up against the usual multilingual edge cases in Hindi and Marathi.
Report
Maker
@zzet1032068 Thanks, İzzet! Glad you noticed the latency—that's something we've spent a lot of time optimizing. Hindi and Marathi edge cases are an active area of evaluation, and we're continuously improving domain-specific performance as we expand our language coverage.
Report
The voice agent felt surprisingly natural in Hindi, which is rare to see from India-based tools. Curious how it handles noisy call center environments in production.
Report
Maker
@zerdabiricjhjd Thanks, Zerda! Noisy call environments are definitely one of the production scenarios we're optimizing for. Real-world telephony conditions are very different from clean demos, so that's a major focus for us.
Report
The voice agent handled my messy Hindi-English mix surprisingly well, which is rare. Curious how it holds up with more complex workflows.
Report
Maker
@brawzb4 Appreciate you trying it, Büşra! Code-switching between Hindi and English is common in real conversations, so handling mixed-language interactions naturally has been one of our priorities. We're also working on supporting more complex multi-step workflows.
Report
Tried the voice agent demo and it actually handled my rambling follow-up questions without losing track, which is more than I can say for most bots. The domain-specific LLM angle feels like a smart move for Indian businesses tired of generic responses.
Report
Maker
@nevinbavbek Thanks, Nevin! Maintaining context across longer conversations is something we care a lot about. We also believe domain-specific AI delivers much better business outcomes than generic assistants, so that's the direction we're continuing to invest in.
Report
finally checked out Studio Form and the voice agent setup was smoother than i expected, handled a sample customer call without me babysitting it.
Report
Maker
@dloker20536 Thanks, Dursun! Happy to hear the setup felt smooth. One of our goals is to reduce the amount of manual configuration needed so teams can get a production-ready voice agent running quickly. We'll keep improving reliability as we add more real-world integrations.
Report
Maker
One question for everyone building with AI:
What's been your biggest challenge in taking an AI prototype into production?
Is it reliability, latency, evaluations, cost, integrations, or something else?
We'd love to learn from the community and build solutions around real-world challenges. Looking forward to hearing your thoughts!
Spent a few minutes playing with their voice agent and the latency felt surprisingly snappy for a domestic build. Curious how their domain LLMs hold up against the usual multilingual edge cases in Hindi and Marathi.
@zzet1032068 Thanks, İzzet! Glad you noticed the latency—that's something we've spent a lot of time optimizing. Hindi and Marathi edge cases are an active area of evaluation, and we're continuously improving domain-specific performance as we expand our language coverage.
The voice agent felt surprisingly natural in Hindi, which is rare to see from India-based tools. Curious how it handles noisy call center environments in production.
@zerdabiricjhjd Thanks, Zerda! Noisy call environments are definitely one of the production scenarios we're optimizing for. Real-world telephony conditions are very different from clean demos, so that's a major focus for us.
The voice agent handled my messy Hindi-English mix surprisingly well, which is rare. Curious how it holds up with more complex workflows.
@brawzb4 Appreciate you trying it, Büşra! Code-switching between Hindi and English is common in real conversations, so handling mixed-language interactions naturally has been one of our priorities. We're also working on supporting more complex multi-step workflows.
Tried the voice agent demo and it actually handled my rambling follow-up questions without losing track, which is more than I can say for most bots. The domain-specific LLM angle feels like a smart move for Indian businesses tired of generic responses.
@nevinbavbek Thanks, Nevin! Maintaining context across longer conversations is something we care a lot about. We also believe domain-specific AI delivers much better business outcomes than generic assistants, so that's the direction we're continuing to invest in.
finally checked out Studio Form and the voice agent setup was smoother than i expected, handled a sample customer call without me babysitting it.
@dloker20536 Thanks, Dursun! Happy to hear the setup felt smooth. One of our goals is to reduce the amount of manual configuration needed so teams can get a production-ready voice agent running quickly. We'll keep improving reliability as we add more real-world integrations.
One question for everyone building with AI:
What's been your biggest challenge in taking an AI prototype into production?
Is it reliability, latency, evaluations, cost, integrations, or something else?
We'd love to learn from the community and build solutions around real-world challenges. Looking forward to hearing your thoughts!