Dograh - The open source VAPI alternative
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Closed voice platforms make you rent your own agents. Dograh is completely open source- nothing is gated. Visual flow builder, add your model key across 30+ integrations or use local models, telephony, human transfer, and advanced QA & monitoring - all free to self-host in one command. Also connect your claude code with MCP to build voice agents for a use case or call recordings.

Replies
Triforce Todos
Dograh
@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
Dograh
Thanks @abod_rehman . we are obsessed with dev and oss ecosystem and are all devs ourselves as well
Dograh
@abod_rehman Thanks, Abdul! We wanted developers to have the flexibility to choose their own models without being locked into one provider.
Premation
Open source voice agents with this much flexibility is 🔥 The fact that you can self-host, use local models, and connect Claude Code via MCP makes this especially interesting. Congrats on the launch! 🚀
Dograh
@isroiljon - Thank you so much for your kind words.
We have given a lot of thought to creating the product and making it easy for developers and business owners alike to create and manage their voice agents. We are always hungry for more product feedback on how we can improve it and make it easier.
Wishing you all the best with @Premation
Dograh
@isroiljon Appreciate you checking it out! Would love to hear what you build with Dograh.
Dograh
thanks @isroiljon . do try our MCP's - we try to give a blowout experience to devs
Dograh
@isroiljon Thanks a lot. The product development has been very deliberate and thus difficult at times. We owe the good mix of highly relevant capabilities it to the early adopters a lot! Looking forward to @Premation doing wonders.
Api Hunt
As a CTO/Solution Architect, I checked how Dograh delivered the outcome and am very happy with them.
Best of luck.
Dograh
@kasaei - Thank you so much for your kind words. We are always hungry for feedback. All the very best with @Api Hunt
Dograh
@kasaei That means a lot from a background like your's. Thank you. Wishing @Api Huntthe best!
Dograh
@kasaei Thanks for the support and kind words. It means a lot!
Dograh
Thanks @kasaei - glad to hear this from you :)
Smallest.ai
Dograh
@devansh_pawan1 - Thank you so much for your support. You guys have done excellent work with @Smallest.ai and we are very happy and proud partners.
Dograh
@devansh_pawan1 Thanks for the support! Great to be partnering with @Smallest.ai.
Dograh
@devansh_pawan1 Thank you for your support. Wishing @Smallest.ai the best!
Documentation.AI
Congrats on the launch. Can teams customize the QA metrics and scoring rules for different industries or call types?
Dograh
@roopreddy - Thank you so much for your message.
Yes, for sure. We not only provided an inbuilt QA node, where you can customise the QA prompt for different industries, call types, and use cases, but we also integrate and play well with other vendors in the space, like Tuner and Noveum.
You can also expose those QA results in your post-call data sync (webhook nodes) so that your systems immediately get updated with how did the call go and how it can be improved.
Hook that with an MCP, and you have got a self-improving agent. All the best with @Documentation.AI
Dograh
@roopreddy Yes, teams can customize the QA prompts and scoring criteria for different industries, call types, and use cases. Results can also be synced to external systems through post-call webhooks.
Dograh
@roopreddy I thought its worth adding that you can define fully custom metrics and thresholds per industry/call type - not just one score, but your own rubric (compliance, script completion, sentiment, etc.) weighted however you want. Combined with the webhook sync above, teams tune scoring to exactly what "a good call" means for their vertical.
FuseBase
Congrats, team! Long-awaited launch! Could you add more built-in observability around latency, token usage, model performance, and call quality?
Dograh
@kate_ramakaieva - Thank you for your message.
Yes, observability and automatic evals creation is something that's on top of our head. We do integrate our basic observability using OTEL exporters on Langfuse, where you can already create data sets for your own use cases.
We are also trying to add these features natively on Dograh and MCP so that observability around latency, token uses, and model performance becomes a first-class citizen of the platform on both Cloud and your self-hosted environments.
Wishing you all the best with @FuseBase
Dograh
@kate_ramakaieva Thanks for the feedback. We’re working toward native observability for latency, token usage, model performance, and call quality across both cloud and self-hosted deployments.
Dograh
@kate_ramakaieva thanks for pushing us in this direction. its definitely a part of our pipeline - and a high priority release
Spur.fit
Congratulations on the launch @sabiha_khan4 ! Curious to know which major sectors you’re seeing initial traction in. Also, are there any limitations around regional languages or specific geographies?
Dograh
@rahul_aluri - Thank you for your message.
We are seeing good traction in Legal Intakes (inbound and outbound), Car Rentals (inbound), Restaurant Booking (inbound) and Medical Insurance (outbound) sectors.
The limitations are mostly around declaring about robo call for automated calls. Supporting regional languages are more of a capability concern and using the right set of models behind the orchestrator.
All the very best with @Spur.fit
Dograh
@rahul_aluri Thanks a lot for your comment. Love what you're doing at @Spur.fit.
Adding on the languages/geography part, since you bring your own models, you can pick the best STT/TTS/LLM per language (70+ supported) rather than being capped by a single vendor's coverage. Geographic reach depends on your telephony provider, and for data-residency-sensitive regions you can deploy in-region or in your own VPC via self-hosting.
Congrats on everything you've been shipping for the fitness coaching space!
Dograh
@rahul_aluri We’re seeing traction in legal, restaurant booking, and medical insurance use cases. Regional language support depends on the STT, TTS, and LLM models you choose, while geographic coverage depends on your telephony provider.
Very interesting! Am I correct in understanding that it’s possible to build a voice AI based on your service and make calls worldwide? I need to make reservations by phone.
Dograh
@natalia_iankovych - Yes. Thats correct. You can build voice agents on top of Dograh and make calls worldwide by connecting it with various telephony providers, like Twilio. You can definitely make reservations by phone.
Dograh
Hi @natalia_iankovych - definitley. You can build voice agents using Dograh for global use cases and in 70+ languages
Dograh
@natalia_iankovych Yes, you can build a voice agent for phone reservations and connect it to telephony for calls worldwide.
Dograh
@mdsahilnoob - Thanks a lot for your support.
Yes, we have almost everything that Vapi has only more. We are always hungry for product feedback and the community is always available to help. See you there!!
Dograh
@mdsahilnoob Thanks for the support! Glad Dograh’s open-source approach resonates.
Dograh
Hi @mdsahilnoob, Absolutely. Cost is a big point.
Our cloud hosted platform is at a flat 1¢/min platform fee with your own provider keys, or you can self-host the open-source build for zero platform fee. Plus hybrid voice (human clips + cloned TTS) can cut latency and cost to a great deal on the underlying usage.
Dograh
Thanks@mdsahilnoob . While both Vapi and retell are great products, but with Dograh you get the flexibility to self host and control costs (dramatically lower with self hosting ) - and also complete ownership of your product (not renting)
Dograh
🚀 MID-DAY UPDATE: Big thanks to @nuseir_yassin1
We’re having an incredible launch day, and we want to give a massive shoutout to Nuseir Yassin (Nas Daily) for stopping by our thread with some sharp questions on voice orchestration!
For anyone following along or asking similar questions about building production-ready AI voice agents with Dograh:
• Seamless Human Handoff: Native escalation and live-agent takeover protocols so your voice agents fall back safely whenever human intervention is needed.
• Bring any Models & Telephony: Easily swap between underlying ai models and telephony providers without changing your stack.
• Developer-First & Open Source: Built by devs, ex CTO's , YC alum - we live and breathe technology and open source
Drop any technical questions below and we’ll answer them live! ⚡