Yes, we offer both white-labeling and on-premise deployment options:
White-labeling: Custom branding, domain, and UI customization
On-premise: Full deployment within your infrastructure These options are available for enterprise customers. Please contact our sales team to discuss your specific requirements.
HIPAA compliant for healthcare applications SOC 2 Type II certified GDPR compliant for handling EU data Regularly audited to maintain these certifications For detailed compliance documentation and reports, please visit our security portal.
Absolutely. Our platform is built to handle high concurrency, and 1000+ concurrent sessions is well within our capacity. We’ve designed our infrastructure to scale horizontally, ensuring reliable performance even during peak usage periods. For enterprise customers with specific scaling needs, we can discuss custom solutions.
Yes, Vapi is designed to achieve low latency, typically around 800 milliseconds for end-to-end voice processing. Our infrastructure is optimized for real-time communication, and we continuously work to minimize latency through various optimizations in our pipeline.
Web Dashboard: It can take minutes to get up & running with our dashboard. Client SDKs: You can start calls with 1 line of code with any of our client SDKs. For more advanced features like function calling, you will have to set up a Server URL to receive and respond to messages.
You could (and the person writing this right now did, from scratch) — but there are good reasons for not doing so.
Writing a great realtime voice AI application from scratch is a fairly challenging task (more on those challenges here). Most of these challenges are not apparent until you face them, then you realize you are 3 weeks into a rabbit hole that may take months to properly solve out of.
Think of Vapi as hiring a software engineering team for this hard problem, while you focus on what uniquely generates value for your voice AI application.
But to address cost, the vast majority of cost in running your application will come from provider cost (Speect-to-text, LLM, Text-to-speech) direct with vendors (Deepgram, OpenAI, ElevenLabs, etc) — where we add no fee (vendor cost passes-through). These would have to be incurred anyway.
Vapi only charges its small fee on top of these for the continuous maintenance & improvement of these hardest components of your system (which would have costed you time to write/maintain).
No matter what, some cost is inescapable (in money, time, etc) to solve this challenging technical problem.
Our focus is solely on foundational Voice AI orchestration, & it’s what we put our full time and resources into.
Not a problem, we can likely already support it. Vapi is designed to be modular at every level of the voice pipeline: Text-to-speech, LLM, Speech-to-text.
You can bring your own custom models for any part of the pipeline.
If they’re hosted with one of our providers: you just need to add your provider keys, then specify the custom model in your API requests. If they are hosted elsewhere: you can use the Custom LLM provider and specify the URL to your model in your API request.
If you are a developer building a voice AI application simulating human conversation (w/ LLMs — to whatever degree of application complexity) — Vapi is built for you.
Whether you are building for a completely “turn-based” use case (like appointment setting), all the way to robust agentic voice applications (like virtual assistants), Vapi is tooled to solve for your voice AI workflow.
Vapi runs on any platform: the web, mobile, or even embedded systems (given network access).
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