Voice AI Agent Development Services
Production-grade voice AI agents on real telephony infrastructure, handling inbound and outbound calls with sub-2000ms latency. Projects start at $1,000.
- 5+ YEARS ACTIVE
- 15 AI ENGINEERS
- 10+ AI PRODUCTS SHIPPED ACROSS OUR PORTFOLIO
- GLOBAL DELIVERY FROM BANGLADESH
Voice AI agent development is the practice of building LLM-powered agents that handle live phone calls, inbound and outbound, on real telephony infrastructure. A production voice agent understands natural speech through phone-line noise, answers inside a strict latency budget, and lets callers interrupt mid-sentence. For your team, that replaces static IVR trees and outsourced call scripts with an agent that resolves calls end to end and escalates with full context. Riverborn is a voice AI agent development company that ships these systems on real telephony, not a demo environment. We run the same stack in production on Dhoni (the enterprise evolution of Vocalo.ai), with 100K+ live voice interactions handled.
Voice is the hardest conversational channel to ship well. A chatbot can take three seconds to reply and lose nothing. On a phone call, that same pause loses the caller. Every response must clear speech recognition, reasoning, and speech generation inside a sub-2000ms budget, through background noise, accents, and interruptions. Riverborn engineers for that reality, delivering telephony-grade voice agents to CTOs, VPs of Engineering, and Heads of CX at Series A to C companies and global enterprises.
What Your Team Gets
on real telephony, not a browser-based demo.
from live calendar availability checks to knowledge-grounded answers that stay current.
with barge-in handling so callers can interrupt naturally.
tuned for phone-line audio conditions, not clean studio input.
across the languages your customer base actually speaks.
for every conversation.
via REST API, so bookings and call outcomes write back into Salesforce, HubSpot, your booking system, or your dialer.
What We Build: Voice Agent Types
Eight voice agent architectures, matched to the shape of your call volume, not the other way around. Riverborn delivers custom voice AI agent development services across each type.
Inbound Support and IVR Replacement Agents
Answer inbound calls with natural conversation instead of a phone tree. The agent understands the caller's request in open speech, retrieves grounded answers from your knowledge base, and resolves routine requests end to end. Calls that need a human route to the right queue with full context attached, not a cold transfer.
→ See also: customer support and CXBooking and Appointment Handling Agents
Take bookings, reschedules, and cancellations over the phone, end to end. The agent checks live availability in your calendar or booking system, confirms the slot with the caller, and writes it back automatically. Every missed call is a lost booking; this agent answers all of them. Hospital, hostel or any kind of service that needs booking.
FAQ and Q&A Voice Bots
Answer the repetitive questions that dominate inbound volume: hours, pricing, policies, order status, and account basics. Grounded in your knowledge base via RAG, so answers stay accurate as your content changes. Routine calls resolve instantly, and human agents only take the conversations that need them.
Outbound Calling Agents
Run outbound campaigns for appointment reminders, payment follow-ups, lead qualification, and re-engagement, at a volume your team could not staff manually. Every call follows a compliant script structure with clear opt-out handling. Outcomes write back into your CRM automatically.
→ See also: AI for sales teamsVoice-Enabled Internal Agents
Employee-facing voice agents for HR and IT helpdesk questions: leave balances, benefits lookups, password resets, ticket status. Retrieves from your internal knowledge base via RAG and escalates to a human when the request falls outside its scope.
→ See also: AI for HR and people operationsMultilingual Voice Agents
Deploy the same agent logic across multiple languages without rebuilding the conversation design for each one. Speech recognition and generation are tuned per language and dialect, so callers get a natural experience regardless of which language they speak.
Voice Analytics and QA Agents
Score every call against your quality rubric automatically: compliance language, sentiment, resolution outcome, escalation triggers. What used to require manual call sampling runs on 100% of calls instead, with exceptions flagged for human review.
Voice-Embedded Product Features
Voice interfaces embedded directly into your own product, in-app voice assistants, voice-driven search, or hands-free workflows for your end users. Ships as an API-integrated feature inside your existing application, not a standalone destination.
Our Technical Approach
Gartner projects that conversational AI will reduce contact center agent labor costs by $80 billion in 2026 alone. That saving only materializes when the underlying architecture handles real phone-line audio conditions, not clean microphone input from a demo.
Riverborn designs every voice agent on a five-stage pipeline. Each stage is documented so your engineering team owns it post-handover.
Voice Pipeline Architecture Layers
Telephony ingestion
Calls connect via Twilio, custom SIP trunking, or your existing telephony provider. Inbound and outbound call flows are configured against your number pool and routing rules.
Speech-to-text
Real-time STT converts caller audio to text as the conversation happens, tuned for phone-line audio quality rather than studio conditions.
LLM reasoning and dialogue management
The agent reasons over conversation state and your grounded knowledge base, decides what to say next, and determines when a tool call, transfer, or escalation is required.
Text-to-speech
The agent's response generates as natural speech, with voice selection and pacing tuned for the deployment context.
Guardrails
Every turn runs through compliance checks, PII redaction where required, and escalation triggers before the conversation proceeds.
Latency and Turn-Taking Architecture
Riverborn engineers the full voice-to-voice loop, speech-to-text, reasoning, and speech generation, to a sub-2000ms p95 response budget. Long pauses are where phone conversations break down, so every pipeline stage is measured against that budget. Barge-in handling ships as a default, not an afterthought. A caller who interrupts mid-response gets heard immediately, rather than talking over an agent that keeps going.
Session and Memory Architecture
Voice sessions carry call-specific state: caller identity where available, conversation history within the call, and any prior interaction history your CRM exposes. For outbound campaigns, the agent carries context into the call, so a follow-up call references what was discussed previously instead of starting cold every time.
LLM-Native Voice Agents vs Traditional IVR
Input handling
LLM-native voice agent
Understands open, natural speech
Traditional IVR
Requires keypad input or fixed phrase matching
Conversation flow
LLM-native voice agent
Multi-turn, reasons over context
Traditional IVR
Fixed menu tree, no memory between steps
Knowledge access
LLM-native voice agent
Retrieves from your knowledge base via RAG
Traditional IVR
Static, pre-recorded prompts only
New use cases
LLM-native voice agent
Update the knowledge base; no re-recording
Traditional IVR
Re-record prompts and rebuild the call flow manually
Caller experience
LLM-native voice agent
Natural conversation, barge-in supported
Traditional IVR
Caller waits for the full prompt before responding
Escalation
LLM-native voice agent
Context-aware handoff with conversation summary
Traditional IVR
Cold transfer with no context passed to the agent
Industries & Use Cases
Riverborn has shipped voice AI deployments across regulated and high-call-volume verticals. The patterns below are active deployment architectures. Each cell links to a fuller industry solution page.
Healthcare & Life Sciences
Appointment scheduling, insurance verification, and post-visit follow-up calls integrated with your EHR via REST API.
→ Voice AI for healthcareFinancial Services & Fintech
Account inquiries, payment reminders, and dispute intake with cardholder data handled inside a compliant call flow.
→ Voice AI for financial servicesE-commerce & Retail
Order status, delivery updates, and return initiation handled by phone at volumes that scale with seasonal demand.
→ Voice AI for e-commerce and retailSaaS & Technology
Inbound support call deflection and outbound onboarding calls for new accounts, grounded in your product documentation.
→ Voice AI for SaaS and technologyManufacturing & Supply Chain
Supplier coordination calls and scheduling confirmations that route exceptions to the right operations contact.
→ Voice AI for manufacturingReal Estate & PropTech
Lead qualification calls, viewing scheduling, and tenant maintenance intake integrated with your CRM and property management system.
→ Voice AI for real estate and PropTechTechnology Stack
Every voice agent ships on the production-validated stack below.
| Category | Technologies |
|---|---|
Telephony | TwilioCustom SIP trunkingCarrier-direct integration where required |
Speech-to-Text | Real-time STT tuned for phone-line audio conditions |
Text-to-Speech | Natural voice generation with configurable pacing and voice selection |
LLM Models | GPT-4oClaude Sonnet 4Llama 3.1 70B |
Orchestration | PipecatLiveKit |
Vector Databases | Pinecone (managed)Weaviate (self-hosted)pgvector (PostgreSQL) |
Enterprise Connectors | SalesforceHubSpotZendeskServiceNowcustom dialer integration via REST API |
Cloud Infrastructure | Pipecat CloudLiveKit CloudCerebriumAWSGCP |
Evaluation & Guardrails | RAGAS frameworkGuardrails AIPII redactioncall recording and audit trail |
Telephony
Speech-to-Text
Text-to-Speech
LLM Models
Orchestration
Vector Databases
Enterprise Connectors
Cloud Infrastructure
Evaluation & Guardrails
How It Works: Our Development Process
Riverborn delivers voice AI agent development through a five-step process. Standard engagements complete in 7 to 12 weeks. Projects start at $1,000 for a focused single-use-case build. Enterprise deployments with multilingual or compliance scope typically run higher and are scoped during discovery.
Discovery and Call Flow Design
We map your call volume, use cases, telephony provider, and compliance scope. Call flow architecture and escalation paths are documented before engineering begins.
DELIVERABLE
Voice Agent Architecture Blueprint with call flow diagrams.
Knowledge Base and Dialogue Design
Our engineers build the RAG pipeline over your knowledge sources and design the dialogue management logic for each use case in scope.
DELIVERABLE
Knowledge retrieval system and dialogue flows in staging.
Voice Pipeline Build and Integration
We build the telephony integration, STT/TTS pipeline, and CRM or dialer connections. You get weekly build demos with live call testing so nothing drifts off-spec.
DELIVERABLE
Voice agent in staging, handling live test calls end to end.
Testing, Guardrails and Compliance
Automated evaluation runs against real call transcripts. Edge-case testing covers background noise, accents, and interruption handling. Compliance verification runs against your regulatory scope. Load testing validates the sub-2000ms p95 target under concurrent call volume.
DELIVERABLE
Production-ready voice agent with evaluation report and compliance documentation.
Deployment and Monitoring
We deploy to production telephony infrastructure with call monitoring, transcription logging, and quality dashboards in place.
DELIVERABLE
Live voice agent with monitoring instrumentation and handover documentation.
Why Riverborn
Grand View Research values the global AI voice agents market at $2.54 billion in 2025, projected to reach $35.24 billion by 2033 at a 39.0% CAGR, with inbound voice agents holding the largest revenue share at 52.1%. Most of that spend will route to vendors who can prove production telephony experience, not a browser demo. Riverborn builds, and runs the same voice architecture on its own product that it ships to clients.
PRODUCTION PROOF
Dhoni is the production proof, not a case study.
Dhoni, the enterprise evolution of Vocalo.ai, has handled 100K+ live voice interactions on real telephony infrastructure. The latency, barge-in handling, and call reliability your team gets is the same architecture running in Dhoni today, not a scaled-down version built for a pitch.
PHONE-LINE REALITY
Built for phone-line reality, not demo conditions.
Background noise, accents, interruptions, and dropped words are the normal case on a phone line, not the exception. Riverborn architects the STT and dialogue layers for that reality from day one, rather than tuning against clean audio and hoping production holds up.
COMPLIANCE BY DEFAULT
Compliance and audit trail as a default, not a retrofit.
Every voice agent ships with call recording, transcription, and PII redaction where required. HIPAA-compliant and PCI-DSS-compliant deployment patterns apply where your compliance posture requires them.
COST STRUCTURE
A cost structure that pays for the rigor.
Our Bangladesh delivery model gives you a 40 to 60% cost reduction vs US and EU agencies at identical production-grade benchmarks. Structural advantage, not a discount on quality. Projects start at $1,000.
4.8+ avg.
product rating
Dhoni + Vocalo.ai
our own voice products in production
100K+
voice interactions handled
Sub-2000ms
p95 latency SLA
HIPAA + PCI-DSS
compliant deployment patterns
RAGAS
eval suite on every build
Related Capabilities
Text-based conversational interfaces on web and mobile
AI Chatbot Development
For conversational systems that route user queries, handle standard FAQs, and ingest structured documents.
Learn moreAutonomous multi-step task execution beyond conversation
AI Agent Development
For autonomous agents that invoke APIs, self-correct, and run multi-step backend workflows.
Learn moreConfirming feasibility before committing to a build
AI Consulting & Strategy
If you're confirming whether voice fits your business case before starting engineering.
Learn moreFrequently Asked Questions
Voice AI agent development is the practice of designing and deploying LLM-powered agents that handle live phone conversations over real telephony infrastructure. It combines a telephony layer, real-time speech-to-text, LLM-based reasoning and dialogue management, text-to-speech, and compliance guardrails. Unlike a traditional IVR, the agent understands open speech and reasons over context rather than matching fixed menu options.
Riverborn projects start at $1,000 for a focused single-use-case build. Final cost depends on call volume, telephony complexity, number of languages, integration count, and compliance scope. Our Bangladesh delivery model keeps costs 40 to 60% below comparable US and EU agencies.
Standard engagements run 7 to 12 weeks across discovery, dialogue design, build, testing, and deployment. Multilingual or high-compliance deployments typically extend that timeline, scoped during discovery.
Traditional IVR routes callers through a fixed menu tree using keypad input or simple phrase matching, with no memory between steps. An LLM-native voice agent understands open, natural speech, reasons over multi-turn context, retrieves grounded answers from your knowledge base, and hands off to a human with full conversation context attached rather than a cold transfer.
Yes. Riverborn builds outbound voice agents for appointment reminders, payment follow-ups, lead qualification, and re-engagement campaigns, with compliant script structure and clear opt-out handling. Call outcomes write back into your CRM automatically.
Yes. Riverborn deploys multilingual voice agents where speech recognition and generation are tuned per language and dialect, so the same underlying dialogue logic serves callers across your full customer base without a separate rebuild per language.
Yes. Riverborn ships HIPAA-compliant and PCI-DSS-compliant voice deployments with call recording, transcription, PII redaction, and audit trail generation per call. Full industry coverage is at AI for healthcare and AI for financial services.
Riverborn integrates via Twilio, custom SIP trunking, and carrier-direct integration where required. Voice agents connect into your existing number pool and routing rules rather than requiring you to migrate telephony providers. For broader system integration, see AI integration services.