Dograh - The open source VAPI alternative

@seomaxtech Thank you for your message.

Our cloud offering is priced at 1 cent per minute of calling if you bring your own keys for models compared to around 5 cents per minute from Vapi and Retell.

If you use Dograh managed models, our model usage is priced at around 7 cents per minute compared to around 8 - 12 cents per minute from Vapi and Retell.

@seomaxtech Our cloud offering costs $0.01 per minute with your own model keys, compared with around $0.05 per minute for Vapi and Retell. With Dograh-managed models, it is around $0.07 per minute, compared with roughly $0.08 to $0.12 per minute. And we can go much lower with an increase in volume.

@seomaxtech to summarise what the team said - self-host it and it's free forever, or use our cloud at 1¢/min + model usage. Your call on ownership vs. convenience :)

Thanks @seomaxtech . With your own model keys, Dograh is ~$0.01/min vs ~$0.05/min on Vapi/Retell.

@huisong_li - Thank you so much for your comment. Good luck with @HarnessRouter ❤️

Thanks for the support  @huisong_li 

thanks @huisong_li for your support :)

@huisong_li Thanks for the support! Wishing you and HarnessRouter all the best. ❤️

@shantanusewu - Thanks a lot for your support. ❤️

Please do not hesitate to reach out if you need any support in implementing Voice AI for your use cases.

Hi @shantanusewu thats such a lovely remark. Would love to connect on other platforms as well . we love IITD :)
Here's lin: https://www.linkedin.com/in/priteshkr/

@shantanusewu Thanks for the support! Really appreciate you rooting for Dograh and the founders. ❤️

@shantanusewu Thanks

@brucem80 This means a lot, genuinely. Thanks for sticking with us these past few months :)

@brucem80 Thanks Bruce! Glad to hear Dograh and our support have been useful.

@brucem80 - Thanks a lot for your kind words ❤️

You will always find us here trying to evangelise and promote Open Source voice AI adoption. You will always find help on our Slack Community.

Thanks@brucem80 ! Great to hear you’ve had a good experience with the product and team.

@dipanshu_kushwaha5 Thanks for your message.

Yes. 100%. Dograh is to voice agents what @n8n is to workflow automation. You can either decide to visually build voice agent using Dograh UI or you can use MCP tools offered by Dograh (cloud or self hosted) to talk to your coding agents to build an agent for you. And all of these play really well with various telephony providers so you can go to production with least friction.

@dipanshu_kushwaha Yes, you can build voice agents visually in Dograh without writing code. You can also use Dograh’s MCP tools with coding agents if you prefer.

@dipanshu_kushwaha5 To add one more layer - it's no-code even after you build. There's a Test Chat mode where you can edit or replay any turn in a past conversation and Dograh regenerates the agent's replies and node transitions from that point, so you can debug and refine logic without touching code. Makes it easy for non-technical folks (support/ops teams) to actually own the agent long-term, not just the initial build.

Yep @dipanshu_kushwaha5  , it’s fully no-code, with visual building and testing built in.

@abod_rehman Thank you for your message.

We are developers at heart, and we are creating this product for the developer community and business owners who want to own their voice AI stack.

Wishing you loads of luck with @Triforce Todos

Thanks @abod_rehman . we are obsessed with dev and oss ecosystem and are all devs ourselves as well

@abod_rehman Thanks, Abdul! We wanted developers to have the flexibility to choose their own models without being locked into one provider.

@abod_rehman thanks! What matters more than the count is that switching is a config change rather than a rewrite; different TTS mid-project, no change to your agent logic. Same mechanism if you want to point at a model on your own hardware.

@aj_123 - Thanks a lot for your support.

Wishing you loads of success and luck with @Tough Tongue AI

Thanks @aj_123 . lovely to see you rooting for us

@aj_123 Thanks for the support! 🙌

@aj_123 Thank you. Rooting for @Tough Tongue AI

@adam_maceachern1 - Thank you so much for the support.

We are always hungry for the feedback. Please let us know if you get a chance to try out @Dograh

@adam_maceachern1 Thanks a lot.

@adam_maceachern1 Thanks for the support! Glad you liked Dograh.

thanks @adam_maceachern1 . glad to you found it great

@kumar_gautam Thank you for your message.

These are some very relevant questions. We connect over Websocket for TTS and STT, so any failure over websocket connection is automatically retried. For LLMs, we have fallbacks in place, so that if our primary LLM takes longer to respond or fails to respond, there are fallback LLMs in place.

I welcome you to try out @Dograh

@kumar_gautam WebSocket failures for STT and TTS are retried automatically, while LLM timeouts or failures trigger fallback models.

@kumar_gautam thanks for the detailed question. Curious what end to end TTFB you're aiming for. if you're benchmarking us against something, I'd genuinely like to hear where we fall short.

@abhishek_ambad - Thanks a lot for your support.

Wishing you all the best for @EmbedAI

@abhishek_ambad Thanks for the support! Glad the self-hosted approach resonates.

@abhishek_ambad Absolutely. Self hosting capability is one of our core priorities. Thanks for the support. All the very best for @EmbedAI!

Thanks @abhishek_ambad . Dograh is definitely a great self hostable voice agent platform for enterprises . We have seen multiple deployments by public sector companies in last couple of months including enterprises in geographies like US, Taiwan, Australia, Philippines etc