In-app voice assistant
Users talk to your product instead of clicking through it, and the assistant runs actions through your API with their permissions.
AI Voice Agents · SaaS
Voice AI Development for SaaS Products
Add real-time voice to your app or platform: conversations that respond fast, handle interruptions and call your product's own APIs. Built on the voice stack that fits your latency and cost targets.
Overview
Voice AI development for SaaS, from API to production
Voice is the feature users ask for and teams underestimate. Wiring a speech-to-text API to a language model and a voice takes an afternoon. Making it feel like a conversation takes real engineering: answers that start fast, a user who can interrupt mid-sentence, accents and background noise, and a cost per minute that still leaves you a margin. Voice AI development for SaaS is the work of getting all of that right inside your product.
We build voice in two shapes. The first is voice inside your app: a coach, tutor, sales trainer or hands-free assistant that users talk to on web or mobile. The second is voice as a feature you sell: AI phone agents your customers configure in your dashboard to answer their calls, book meetings or qualify leads. Both run on streaming speech recognition, a language model with access to your product's tools, and natural speech synthesis, connected through your APIs so the agent can actually do things.
We have shipped this before. Arthur is a text and real-time voice AI coach built on 30+ books, working in English and German and used by thousands of women. The same patterns apply to your product: low-latency streaming, turn-taking that handles interruptions, multilingual speech and transcripts your team can review. We pick the stack per project, whether that's a managed voice platform like Vapi, an open framework like LiveKit, or Twilio for phone numbers, and we model the per-minute cost before you commit.
Use cases
AI Voice Agents use cases in SaaS
AI phone agents as a product feature
Let your customers set up AI agents that answer their calls, book appointments or qualify leads, managed from your dashboard.
Voice coaching and training apps
Role-play, coaching and practice conversations that respond in real time, like the voice mode we built for Arthur.
Voice AI MVP
A working voice prototype on a real number or in a real app, fast enough to test with pilot users and show investors.
Call summaries and notes
Transcribe sales, support or onboarding calls and turn them into summaries, action items and CRM updates.
Multilingual voice support
Serve users in English, Arabic, German, Urdu and other languages from one voice agent that detects and switches language.
How it works
How it works
- 01User speaksThrough a mic button in your web or mobile app, or by calling a phone number connected to your platform.
- 02Speech is transcribed as it streamsStreaming speech recognition turns audio into text while the user is still talking, so the reply can start sooner.
- 03The model decides what to doA language model reads the request with the user's context and chooses whether to answer, ask a follow-up or call one of your tools.
- 04Your API does the workThe agent creates records, looks up accounts or books slots through your product's own endpoints and permissions.
- 05It replies in a natural voiceSpeech synthesis streams the answer back. If the user interrupts, the agent stops and listens.
- 06Everything is logged and meteredTranscripts, tool calls and minutes are stored per tenant for support, analytics and usage-based billing.
Capabilities
Key features
Low-latency streaming
Each stage streams, and we measure end-to-end response time so conversations don't feel laggy.
Interruption handling
Users can cut in mid-answer, the way they would with a person, and the agent responds to what they just said.
Tool calling into your product
The voice agent uses the same APIs and permission checks as your app, so it can act, not only talk.
Multi-tenant configuration
Each customer gets their own prompts, voice, knowledge and phone numbers, isolated from every other tenant.
Multilingual speech
English, Arabic, German, Urdu and many more, with language detection and switching mid-conversation.
Per-minute cost tracking
Usage is metered by tenant and feature, so you can price voice profitably and spot expensive patterns early.
Integrations
Works with your SaaS stack
- OpenAI
- Google Gemini
- Anthropic Claude
- Vapi
- LiveKit
- Twilio
- Next.js
- React Native
- Stripe
- AWS
Using something else? If it has an API, a database or a webhook, we can connect to it.
Outcomes
Benefits for SaaS teams
A feature customers will pay for
Voice is a visible upgrade you can package as a premium tier or add-on.
Faster time to market
We've already solved the latency, turn-taking and telephony problems, so you skip months of trial and error.
Margins you understand
Cost per minute is modelled before the build and tracked after launch, so voice doesn't quietly eat your gross margin.
Freedom to switch providers
We design the voice layer so speech, model and telephony providers can be swapped as prices and quality change.
Our work
Proven Voice AI Product Work
FAQ
AI Voice Agents for SaaS: FAQs
How do I add voice AI to my app?
You connect three streaming pieces: speech recognition, a language model with access to your app's functions, and speech synthesis, plus a real-time transport such as WebRTC. The hard part is tuning latency and interruptions, and making the agent call your APIs safely. That's the work we do.
Should we use Vapi, LiveKit or build our own voice stack?
It depends on your volume and how much control you need. Managed platforms like Vapi get you live fastest, while LiveKit and a custom pipeline give more control over cost and data at scale. We recommend one after looking at your use case and expected minutes.
How much does voice AI cost per minute?
It depends on the speech recognition, language model, voice and telephony providers you choose, and on how long the conversations run. We model the per-minute cost for your traffic before the build so you can price the feature with confidence. Book a call and we'll walk through it.
How fast does a voice AI agent respond?
Fast enough to feel conversational when it's built well. We stream every stage, keep prompts and tool calls lean, and measure response time on real calls rather than relying on provider benchmarks.
Can a voice agent speak more than one language?
Yes. Arthur runs real-time voice conversations in English and German, and we build agents in Arabic, Urdu and many other languages, with switching mid-call where it's needed.
Is it legal to use AI voice agents for outbound calls?
It depends on where you call. In the US, the TCPA restricts automated and artificial-voice calls without prior consent, and in the EU and UK, GDPR governs call recording and personal data. We build consent capture, disclosure and opt-out handling in, and your legal team confirms the final rules.
How long does a voice AI MVP take?
Usually a few weeks for a focused agent on one workflow. Multi-tenant configuration, telephony for your customers and usage billing add time. We set a timeline after discovery.
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ExploreFurther reading
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Your users want to talk. Let them.
Tell us where voice fits in your product. We'll show you a working voice agent and the per-minute numbers behind it.