A voicebot handles phone conversations the way a human agent does -- understanding natural language, asking clarifying questions, retrieving information, and completing tasks -- without putting callers on hold.
We build voicebots for inbound call handling, outbound campaigns, and interactive voice applications. Speech-to-text, intent recognition, dialogue management, and text-to-speech integrated into a system that sounds natural and actually resolves caller needs.
Inbound voicebots for customer support, scheduling, and information queries
Outbound voicebots for surveys, reminders, and appointment confirmation
Natural conversation flow -- not IVR menus, not press-1-for options
Integration with your CRM, helpdesk, booking system, and telephony infrastructure
RaftLabs builds voicebots that handle real phone calls: inbound customer support, appointment scheduling, information queries, and outbound reminder and survey campaigns. We integrate speech-to-text (Deepgram, Google Speech-to-Text, Whisper), LLM-based intent recognition and dialogue management, and natural text-to-speech via ElevenLabs or OpenAI TTS. Every voicebot connects to your telephony provider (Twilio, Vonage, Genesys), CRM, and booking systems, and includes a live agent handoff path. A focused inbound voicebot for one use case typically costs $30,000 to $65,000.
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Calls that resolve, not calls that hold
The goal of a voicebot isn't to replace human agents. It's to handle the routine, repeatable calls that don't need a human agent -- so your agents spend their time on calls that do.
We build voicebots that actually resolve caller needs, not voicebots that frustrate callers into asking for a human anyway.
Capabilities
What we build
Inbound customer support voicebots
Voicebots that handle inbound customer calls end-to-end without transferring to an agent for the routine queries that make up 60-70% of call volume: account balance and status queries, order tracking, basic product questions, appointment confirmation, and policy lookups. Natural language understanding built on Dialogflow CX, AWS Lex, or a custom NLP layer handles how customers actually talk -- colloquial phrasing, incomplete sentences, mid-call corrections -- not just menu keyword matching that frustrates callers into immediately pressing zero.
Speech recognition uses Google Cloud Speech-to-Text or AWS Transcribe Streaming for sub-second transcription with domain-specific vocabulary adaptation: your product names, internal codes, and industry terminology are added to the recognition vocabulary so they transcribe accurately rather than being phonetically guessed as common words. Text-to-speech uses ElevenLabs, Google Wavenet, or Amazon Polly Neural voices for natural-sounding prompts -- not robotic TTS that signals a poor-quality deployment. Latency target: under 500ms end-to-end from caller utterance end to bot response start, achieved by streaming STT transcription (processing begins before the caller finishes speaking) and response pre-generation for high-frequency intents. CRM integration (Salesforce, HubSpot, Zendesk) personalises responses with the caller's account data: name, order history, current status, recent interactions. For questions outside the voicebot's scope, graceful handoff to a live agent transfers the call with a structured context summary -- account details, intent identified, information already gathered -- so the agent doesn't start from scratch.
Appointment scheduling and reminders
Inbound scheduling voicebots let callers book, change, or cancel appointments through natural conversation -- stating their preferred date and time rather than selecting from a menu -- with availability checked in real time against your scheduling system (Acuity, Calendly, or your custom booking backend). Slot allocation logic applies your business rules: buffer times between appointments, resource constraints (a specific clinician or room required for a specific appointment type), and minimum advance notice for same-day booking. Outbound reminder voicebots call confirmed appointments at configurable intervals (48 hours, 24 hours) and offer self-service rescheduling to callers who can't make their slot -- capturing reschedules without tying up staff time on calls that don't require human judgment. No-show rates drop 25-40% in practices and service businesses with structured reminder campaigns. Waitlist management contacts the first available patient or customer when a cancellation opens. Full integration with your existing booking infrastructure -- no platform migration required.
Outbound survey and campaign calls
Outbound voicebots for post-interaction satisfaction surveys (capturing NPS or CSAT scores and verbatim comments at scale -- voice surveys achieve 3-5x higher completion rates than email surveys for the same population), payment reminder calls (personalised with amount due and payment options, with self-service payment capture via IVR DTMF or agent transfer for disputes), and reactivation campaigns for churned or lapsed customers. Dynamic script personalisation pulls from your CRM so each call opens with the caller's name, their specific account context, their tenure as a customer, and the relevant offer -- not a generic script applied uniformly to every contact regardless of history. Response capture is structured for immediate CRM writeback and reporting dashboards. Outbound voicebots reach 3-5x the contact rate of manual dialling campaigns at a fraction of the cost. TCPA and local outbound calling compliance built into campaign design: time-of-day restrictions, opt-out handling, and call frequency caps.
Telephony and contact centre integration
Integration with your existing telephony infrastructure so the voicebot adds capability without requiring a platform migration: Twilio Programmable Voice for cloud-native deployments, SIP trunking to on-premises or legacy PBX systems (Avaya, Cisco), Genesys and Amazon Connect for enterprise contact centre platforms, and Vonage for international PSTN coverage. DTMF keypad fallback for callers who prefer pressing numbers over speaking (important for older demographics or noisy calling environments). Call recording configured to comply with jurisdiction-specific consent requirements (two-party consent states, GDPR in the EU). Live agent transfer sends the caller and a structured context packet (identified intent, entities captured, relevant account data) to the agent desktop in your CCaaS platform, so the agent sees what the voicebot collected before the call connects. Real-time transcription for quality assurance and compliance monitoring.
Dialogue design and conversation flows
Conversation design for voicebots that resolve rather than frustrate: intent taxonomy mapped to your actual call types from call recording analysis, not guessed from general categories; entity extraction trained on your domain-specific terminology (product codes, account identifiers, service categories your callers mention by name); graceful reprompting when the caller's response doesn't match the expected answer format (asking for a date, getting a complaint instead); confidence-based routing that escalates low-confidence interpretations before the voicebot acts on a potentially wrong understanding; and barge-in handling that stops the voicebot mid-sentence when the caller has already started speaking. Persona and voice design -- tone, pacing, acknowledgment phrases -- tuned to match your brand and your caller demographics. Dialogue tested on actual call recordings from your operation, not just synthesized test cases.
Analytics and performance monitoring
Voicebot performance dashboards showing the metrics that drive improvement decisions: call volume by intent category, containment rate (percentage of calls resolved without agent transfer -- the headline metric for voicebot ROI), transfer rate with transfer reason breakdown (identifying which intents are leaking to agents and why), average handle time by intent, and caller satisfaction scores from post-call surveys or sentiment analysis on transcripts. Intent gap analysis surfaces high-volume unrecognized intents -- the caller questions the voicebot is failing to handle that would extend containment if added to the dialogue scope. Call recording analysis with automatic transcription for quality review and regulatory compliance sampling. Confidence distribution monitoring identifies when model performance is degrading, typically the first signal before containment rate drops. The monitoring infrastructure that turns launch into a continuous improvement cycle rather than a one-time deployment.
High inbound call volume for routine queries?
Tell us your call types, current volume, and what a resolved call looks like. We'll design the voicebot.
AI Orchestration -- orchestration for complex multi-turn AI workflows
Frequently asked questions
An IVR (Interactive Voice Response) is a menu-driven system -- 'press 1 for billing, press 2 for support'. The caller has to navigate a rigid menu structure to reach the right option. A voicebot understands natural language: the caller says what they need in their own words and the voicebot understands, asks clarifying questions if needed, and resolves or routes the call appropriately. Voicebots are more effective for complex queries, have much higher caller satisfaction, and handle a wider range of inputs. IVRs are faster to build for very simple, predictable call patterns. Most organisations replacing IVRs with voicebots see significant improvement in first-call resolution and caller satisfaction.
We select the speech-to-text (STT) engine based on accuracy requirements, latency constraints, and domain vocabulary. Deepgram: low latency, strong real-time transcription, good for customer service use cases where streaming transcription matters. Google Speech-to-Text: broad language support, strong accuracy, well-documented. OpenAI Whisper: high accuracy, open-source, good for batch transcription. For domain-specific vocabulary (medical terminology, technical product names, regional accents), we evaluate and fine-tune where the general model accuracy is insufficient for your use case.
Natural voice quality requires both good text-to-speech (TTS) and natural dialogue design. For TTS, we use ElevenLabs, OpenAI TTS, or Google WaveNet -- all capable of producing voice that most callers don't identify as AI on first listen. The bigger challenge is dialogue design: a voicebot that sounds robotic isn't the TTS quality, it's unnatural turn-taking, pauses in the wrong places, and responses that feel scripted. We design dialogue flows that handle interruptions, corrections, and conversational context -- not just the happy path.
We integrate with telephony providers through their APIs and SIP (Session Initiation Protocol). Twilio: flexible API, widely used, straightforward integration. Vonage (Nexmo): similar capability to Twilio. Genesys, Avaya, NICE CXone: enterprise contact centre platforms with voicebot integration APIs. Amazon Connect: AWS-native telephony with direct integration to AWS AI services. The integration connects your phone number to the voicebot -- callers dial your existing number, the voicebot handles the call, and transfers to a live agent when needed.
A focused inbound voicebot for a defined use case (appointment scheduling, FAQ handling, or order status) with telephony integration typically runs $30,000--$65,000. A voicebot handling multiple intents with CRM integration, live agent transfer, and analytics runs $55,000--$100,000. Outbound campaign voicebots with dynamic script generation and CRM integration run $25,000--$55,000. Telephony and AI API costs at production volume depend on call volume and duration -- typically $0.05--$0.20 per minute of handled call time.
Work with us
Tell us what you need. We'll tell you what it would take.
We scope Voicebot Development Services in 30 minutes. You walk away with a clear cost, timeline, and approach. No commitment required.
Scope and cost agreed before work starts. No surprises. No obligation.
Working prototype within 3 weeks of kickoff.
Pay by milestone. You see progress before each invoice.
60-day post-launch warranty. Bug fixes, UI tweaks, and deployment support. No retainer.
