LM-Kit OneThe Private AI Application Server
Promoted
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.
Nas.com
How does the human handoff work when an agent reaches a conversation it cannot confidently handle?
Dograh
@nuseir_yassin1 - Thanks for your message.
We have very excellent support for human handoff, where you can declare static destinations or destinations based on the context from the conversation of the agent with the caller. You can define PSTN phone numbers or SIP addresses or ViciDial Ingroups in those destinations where the voice agent can transfer the call based on your matching conditions.
And, of course, have to prompt the LLM to make that transfer call based on certain conditions. If prompted well, the LLM can do it with very high confidence.
Dograh
Hello@nuseir_yassin1 thank you for your message. Adding to Abhishek's reply - the failure path is worth noting too: if the transfer destination can't be resolved (resolver timeout, no match, etc.), it fails gracefully and the agent keeps the conversation pipeline running rather than dropping the call. And for tightening when it hands off, the QA node surfaces signals like repeats, interruptions, and dead air that teams use to refine the confidence logic over time.
Dograh
@nuseir_yassin1 Dograh can hand off to static or dynamically resolved destinations, including phone numbers, SIP addresses, and ViciDial ingroups. The agent dials the destination and waits for an answer before bridging the caller, with configurable transition messages, timeouts, and fallback behavior if the transfer fails.
Dograh
Thanks @nuseir_yassin1 the human handoff is seamless with Dograh - you can create a separate tool for human transfer and attach this to your voice agent (and instruct it to call it when required)
P.S. really appreciate the comment coming from you Nas :)
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.
Dograh
Yes @roopreddy absolutely - metrics and scoring rules can be customized for different call types. Fullly customisable. We are also brining in persona simulations for AI to AI testing of voice agents
At floworks, we tried a few voice agent platforms before landing on Dograh, and the self hosted option made it a no brainer. Feels like it's built by people who actually build voice agents themselves. Excited to see where this goes.
Dograh
@ritesh2503 - Thanks for your appreciation. Yes, we as builders are super passionate about what we are building for the open source ecosystem and community. Our mission is to enable every company in the world to own and operate their voice AI agents securely and efficiently.
Dograh
@ritesh2503 Thanks for the support! Glad the self-hosted approach worked for your team at Floworks. Excited to keep building with feedback from teams using Dograh in production.
Dograh
Thanks Ritesh- we believe in self hosted voice ai and also open weight models. We will keep building for the dev community :)
Dograh
@ritesh2503 you hit the nail on the head. We are our own number one users, so if it didn't work for us first it wasn't shipping :)
Dograh
@brucem80 This means a lot, genuinely. Thanks for sticking with us these past few months :)
Dograh
@brucem80 Thanks Bruce! Glad to hear Dograh and our support have been useful.
Dograh
@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.
Dograh
Thanks@brucem80 ! Great to hear you’ve had a good experience with the product and team.
Zaplingo
The ability to run local models and avoid per-min platform fees is huuuge. But what's best is that the founders are incredibly knowledgeable and always willing to help with setup, best configs or answer any kind of questions. Excited to see where this is going!!
Dograh
@drag0s - Thanks a lot for your kind words ❤️ Wishing you loads of luck with @Zaplingo
Dograh
@drag0s Thanks for the support! Glad the local model support and hands-on help have been useful.
Dograh
@drag0s the founder shoutout is so real, can confirm from the inside :) and it's not just the founders either - our Slack community's got contributors and users constantly trading configuration insights, figuring out the right tool setup for specific use cases, and helping each other debug.
Dograh
Thanks @drag0s . lovely to see you root for us :)
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! ⚡
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 :)