Automate the conversations your agents shouldn't be handling
Resolve customer queries instantly across voice and digital channels, without adding friction or increasing operational complexity. We design and deploy conversational AI that handles high-volume interactions, improves containment, and integrates with your existing environment.
We bring structured methodology to how conversational AI is designed, deployed, and improved
Deliver automation that customers actually use—designed around real interactions, not isolated tools.
We bring strategy, conversation design, and technology into one system, so automation works consistently across channels and continues to improve over time.
Start with the conversations that matter most
Focus automation where it creates real value, based on volume, complexity, and customer effort. We map your interactions end-to-end to identify where automation should be applied, where it shouldn’t, and how it should be designed.
The capabilities that make conversational AI work in production
What we build
Conversational IVR
Replace rigid menu trees with natural language. Deployed in Arabic and English across banking and telco, with 25–35% reductions in handling time — without replacing your existing infrastructure.
Virtual Assistants (Voice & Chat)
Purpose-built virtual assistants for the interactions your agents handle most — account queries, policy checks, claim status, appointment booking. Fully integrated with your CRM and contact center platform.
Agent Assist
Real-time guidance, relevant knowledge, and suggested responses — reducing handling time and improving accuracy on complex calls where automation isn't the right answer.
Use Case Assessment
We identify the top 20% of use cases that carry 80% of business impact, before a platform decision is made. If you've had a previous deployment underperform, we start here.
Conversational IVR
Replace rigid menu trees with natural language. Deployed in Arabic and English across banking and telco, with 25–35% reductions in handling time — without replacing your existing infrastructure.
Virtual Assistants (Voice & Chat)
Purpose-built virtual assistants for the interactions your agents handle most — account queries, policy checks, claim status, appointment booking. Fully integrated with your CRM and contact center platform.
Agent Assist
Real-time guidance, relevant knowledge, and suggested responses — reducing handling time and improving accuracy on complex calls where automation isn't the right answer.
Use Case Assessment
We identify the top 20% of use cases that carry 80% of business impact, before a platform decision is made. If you've had a previous deployment underperform, we start here.
Conversation design, treated as a discipline
AI Trainer
Works with your language models and analytics. Trains and improves NLP over time. The bridge between design and engineering.
Conversation Designer
Maps the customer journey and shapes the dialogue flow. Turns knowledge into an experience, deciding what information comes when, and in what order.
Conversational Copywriter
Defines the persona, tone, and language. The difference between a bot that sounds like a form and one that sounds like a person.
Enterprise-grade conversational AI. Built for your environment
We work across leading conversational AI platforms and align each deployment to your channels, languages, and existing systems.
Kore.ai
Unified enterprise conversational AI, no-code to full-custom, omnichannel, with best-in-class analytics and on-premise deployment flexibility.
Sprinklr
AI-powered conversational platform built into a unified CX suite, enabling automation, engagement, and insights across voice and 30+ digital channels.
XCAI
Arabic-first conversational AI platform trained on regional data, WhatsApp-native, with pre-built models for key industries — low latency and seamless integration with legacy systems across the Middle East.
Botter
WhatsApp-first conversational AI built for Arabic-speaking markets — rapid deployment, strong regional channel integrations, accessible to non-technical teams.
Proven outcomes across regional deployments
Customer stories
UAE Bank — Conversational IVR
Natural language IVR across 5 million calls — without replacing a single existing component. 90% containment on speech-enabled services, 35%+ IVR handling time reduction, 85%+ Arabic speech accuracy including dialects.
Saudi Bank — VIP IVR
Arabic speech recognition that matched English accuracy — at VIP contact centre scale. 5M calls per year handled, Arabic NLP accuracy matched English, zero infrastructure replacement.
Saudi Bank — B2B Assessment
70+ use cases assessed. Top 20% identified before a single platform decision was made. 80% of business impact in top use cases, full prioritisation roadmap, technology brief ready for execution.
UAE Bank — Conversational IVR
Natural language IVR across 5 million calls — without replacing a single existing component. 90% containment on speech-enabled services, 35%+ IVR handling time reduction, 85%+ Arabic speech accuracy including dialects.
Saudi Bank — VIP IVR
Arabic speech recognition that matched English accuracy — at VIP contact centre scale. 5M calls per year handled, Arabic NLP accuracy matched English, zero infrastructure replacement.
Saudi Bank — B2B Assessment
70+ use cases assessed. Top 20% identified before a single platform decision was made. 80% of business impact in top use cases, full prioritisation roadmap, technology brief ready for execution.
Where we typically get involved
- Your IVR hasn’t changed in years, and customers are struggling to navigate it
- You've run a chatbot pilot and the containment numbers didn't come close to what was promised
- You're serving customers in Arabic and finding most platforms don't handle it well at production scale
- You need to select a conversational AI platform and want an assessment that isn't led by the vendor selling it
- You want to automate, but not at the cost of the experience that built your customer relationships
Questions we hear most often
Yes. Advanced NLP models can be trained on Modern Standard Arabic, Gulf, Levantine, and Egyptian Arabic — including natural code-switching with English — achieving over 95% dialect recognition accuracy in production. This requires dedicated regional model training on real data, not adaptation from a generic multilingual model.
MSA models understand formal written Arabic. Dialect-trained models understand how people actually speak — in Gulf, Levantine, or Egyptian Arabic. In the Middle East, most customers communicate in dialect, not MSA, so dialect training is essential for any real-world customer-facing deployment.
Yes, when deployed correctly. Saudi Arabia’s Personal Data Protection Law (PDPL), supervised by SDAIA, governs how customer data is collected, stored, and processed. Compliant deployments require in-country data hosting, consent management, and full audit logging — all engineered into the architecture from day one.
Yes. On-premise and in-country cloud options are available for organizations with strict data sovereignty requirements — particularly in banking, government, healthcare, and telecom across the GCC. Not all global vendors support in-country hosting for the region, so this must be factored into platform selection.