ZTABS builds AI voice agents for Riyadh enterprises — replacing rigid IVR menus with conversational Arabic voice bots that understand Gulf Arabic, navigate Saudi telecom infrastructure, and handle the call volumes of government hotlines and enterprise contact centers.
Saudi Arabia's call centers are enormous. STC alone handles 40+ million customer calls annually. The Ministry of Health's 937 hotline serves the entire Kingdom. Saudi Electricity Company, Al Rajhi Bank, and GOSI each run contact centers with hundreds of agents. These operations share a problem: legacy IVR systems that force callers through 8-10 button-press menus in formal Arabic before reaching a human — if they don't hang up first. Abandonment rates on Saudi IVR systems regularly exceed 40%. The technology to replace this exists: AI voice agents that let callers speak naturally in Gulf Arabic, understand their intent, and either resolve the issue directly or route to the right human agent with full context. But Arabic voice AI has been a hard problem. Gulf Arabic differs substantially from MSA in pronunciation, vocabulary, and sentence structure. Saudi callers use regional dialects — Najdi in Riyadh, Hijazi in Jeddah, Southern dialects in Asir. Most commercial voice AI platforms were built for English and handle Arabic as a poorly tested add-on. Building voice agents that genuinely work for Saudi callers requires Arabic-first speech engineering, not English voice bots with an Arabic language pack.
Riyadh's voice agent demand is driven by Vision 2030's customer experience mandates and the sheer scale of Saudi contact center operations. The Communications, Space & Technology Commission (CITC) reported 1.2 billion customer service interactions in the Saudi telecom sector in 2023. STC, Mobily, and Zain collectively operate contact centers with 5,000+ agents. The government sector is equally massive: the National Unified Number System (199 for government services, 937 for health, 911 for emergency) handles millions of calls from citizens who expect to speak Arabic and get answers, not navigate touch-tone menus. Banking contact centers at Al Rajhi, SNB, Riyad Bank, and Alinma process account inquiries, card services, and loan applications by phone — many elderly Saudi customers strongly prefer voice over apps. Healthcare facilities across Riyadh — KFSH&RC, Saudi German Hospital, Dr. Sulaiman Al Habib — handle appointment scheduling, prescription refills, and insurance queries by phone. Saudi Arabia's contact center outsourcing market (serving companies that outsource their call handling) has grown to SAR 8+ billion, creating demand from BPO operators like Majorel Saudi, TTEC Arabia, and Teleperformance KSA who need AI to serve clients more efficiently.
Our Riyadh voice agent projects start with Arabic speech data. We collect and annotate Saudi caller audio (with consent and proper NDMO data handling) to build speech recognition models that understand how real Saudi customers actually speak — not laboratory Arabic. Gulf Arabic speech recognition requires handling: short vowel dropping (common in Saudi spoken Arabic), dialectal vocabulary (Najdi "وش تبغى" vs MSA "ماذا تريد" for "what do you want"), code-switching between Arabic and English (particularly for brand names, technical terms, and younger callers), and the rapid speech patterns of frustrated callers who have already navigated an IVR. We evaluate Arabic ASR (Automatic Speech Recognition) options: Whisper large-v3 handles Saudi Arabic reasonably well, Google Cloud Speech has Arabic models, and we build custom models for high-accuracy requirements. The NLU (Natural Language Understanding) layer classifies caller intent from transcribed Arabic text — using fine-tuned LLMs that understand Saudi business contexts. For telephony, Saudi contact centers run on Avaya, Genesys, Cisco UCCE, or cloud platforms like Amazon Connect. We integrate via SIP trunking or the platform's API layer — the voice agent sits in front of the existing ACD (Automatic Call Distribution) and routes calls that need humans to the right skill group with full context. TTS (Text-to-Speech) for Arabic uses ElevenLabs or Microsoft Azure Neural Voice with Arabic voice models — we test multiple voices with Saudi focus groups to find ones that callers find natural and trustworthy.
Telecommunications
A Saudi telecom operator handling 12 million customer calls monthly ran a contact center with 1,200 agents. The existing IVR system had 11 menu levels and a 43% abandonment rate. 55% of connected calls were routine inquiries (balance checks, plan details, bill payment status, SIM replacement requests) that followed predictable patterns. Agent attrition was 35% annually — the high-pressure, repetitive work made retention difficult. The operator was spending SAR 180 million annually on contact center operations.
We built an Arabic voice agent that handles the top 8 call categories in conversational Gulf Arabic: balance and usage inquiries (connected to the billing system via API), plan change requests, bill payment status and due dates, SIM replacement initiation, international roaming activation, data package add-ons, service complaint logging, and store location/hours. The voice agent speaks natural Gulf Arabic, understands dialectal variations, and processes voice-note-style speech (callers who speak in long, unstructured sentences). Calls requiring human intervention transfer to a live agent with the full conversation transcript and identified intent — the agent starts the conversation with context, not "how can I help you?"
The voice agent now handles 38% of all inbound calls without human intervention — 4.56 million calls monthly. IVR abandonment dropped from 43% to 12% (callers reach the voice agent in 2 seconds instead of navigating menus). Average handle time for human-assisted calls dropped 28% because agents receive pre-identified intent and context. The operator reduced headcount by 280 agents through attrition (not layoffs) and redeployed 150 agents to upselling and retention roles. Annual contact center cost savings: SAR 52 million.
Human-like phone calls with sub-second latency, natural turn-taking, and emotion-aware responses.
High-volume outbound calling for lead qualification, appointment setting, and follow-up campaigns.
24/7 inbound agents that answer questions, route calls, and resolve issues without hold times.
Real-time integration with Salesforce, HubSpot, Calendly, and custom APIs during live calls.
Automatic transcription, sentiment analysis, call scoring, and performance dashboards.
Intelligent handoff to human agents when calls exceed the AI's scope, with full context transfer.
Riyadh's voice AI market includes Parloa (German, entering MENA), Google CCAI (Contact Center AI, used by some Saudi banks), Amazon Connect (growing presence via AWS Bahrain), and local players like Lucidya (Saudi social listening/engagement platform expanding into voice). Avaya and Genesys offer AI add-ons to their existing contact center platforms — functional for English but Arabic support is weak. Indian BPO operators offer "AI-assisted" call handling that is mostly human agents with scripting tools. The gap is in genuine Arabic conversational AI: voice agents that understand Gulf Arabic dialects, handle Saudi-specific call flows (government services, telecom, banking), and integrate with local telephony infrastructure. ZTABS builds custom Arabic voice intelligence, not English voice bots with an Arabic translation layer.
Voice agent projects in Riyadh range from SAR 150,000 ($40,000) for single-use-case bots (balance inquiries, appointment scheduling) to SAR 800,000+ ($213,000+) for enterprise contact center automation with multi-intent handling and full ACD integration. A Saudi contact center agent costs SAR 6,000-9,000/month fully loaded; 280 agents saved represents SAR 20-30 million annually. ZTABS delivers at competitive rates with Arabic voice engineering that is genuinely rare in the market.
Verified reviews from real client engagements — sourced from our public testimonial archive and Clutch profile.
My experience is throughout positive. Communication, service, the short response times and the flawless execution of a challenging topic was absolutely great. ZTABS is definitely my first choice again.
Christian Neff
Bank Software Advisory · Bank Software Advisory
Fintech
Fantastic Agency! I couldn't fault them even if I tried. They always go above and beyond to meet your expectations and always produces quality work. Thank you ZTABS.
Stephanie Kal
CEO · Beauty Finder Australia
Marketplace
It has been great working with ZTABS. They bounce off the ideas along the way. Amazing Experience.
Joel Rowe
CEO · Drill Quoter
Marketplace
We don't just contract — we ship and operate our own software. 17 products in production.
Common questions about AI voice agent development for Riyadh businesses
Yes, with purpose-built speech models. Gulf Arabic (Najdi, Hijazi, Eastern) differs from MSA in pronunciation, vocabulary, and grammar. We train speech recognition on Saudi caller audio to handle dialectal speech, code-switching, and the informal patterns of real phone conversations. The agent understands "وش سالفة الفاتورة" (Najdi for "what's the story with the bill") as naturally as formal MSA queries.
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AI Voice Agent Development in New York, NYZTABS is a remote-first AI voice agent development agency serving New York businesses — including natural voice conversations, outbound campaign agents, inbound call handling. We work with Finance & Fintech, Media & Advertising, Fashion & Retail companies in New York, NY via timezone-aligned engineers and async workflows; we do not have a local office, and we are explicit about that with every client.
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