AI Chatbot and Agent Development Dubai

AI chatbots and agents engineered to reach production

Custom AI chatbots and AI agents that answer your customers, work with your systems and actually get things done.

10turtle designs, develops and governs conversational AI for businesses in Dubai and across the UAE. From a customer support chatbot on your website to an AI sales agent connected to your CRM, we build systems that are grounded in your business data, integrated with your technology and designed for reliable real world use. Not another chatbot demo. A production system your team and customers can actually rely on.

CustomerrequestAI AGENTreads · decides · actsCRM & ERPKnowledge baseHelpdeskActionresolved ✓
An agent doesn't just answer, it reasons across your systems and closes the loop.

TRUSTED BY TEAMS THAT SHIP

Click any platform to read verified customer reviews.
Beyond the demo

An AI assistant should do more than generate an impressive demo

The easiest part of an AI chatbot project is getting something to talk. The difficult part is making it useful.

Your AI system needs to understand your business. It needs access to the right information. It needs to know what it is allowed to do. It needs to know when it should stop.

And when a human needs to take over, the conversation should not start again from zero.

That is the difference between an AI demo and a production AI system.

We build for the real environment — grounded in your data, connected to your systems, shaped for your customers and your team, with measurable objectives for your business.

Yourdata (grounded in approved information)
Yoursystems (CRM, ERP, helpdesk, APIs)
Yourbusiness (measurable objectives and controls)
Get a Quote
Services

AI chatbot development services in Dubai

We build conversational systems around your business rather than forcing your requirements into a generic chatbot platform. Pick the capability that fits your goal to see how we build it.

AI Chatbot Development

Custom AI chatbots for websites, applications and digital customer experiences that understand natural language and answer from your business information.

AI Agent Development

An AI agent that understands context, makes decisions, uses tools and takes actions across connected systems for multi step workflows.

RAG Chatbot Development

A RAG chatbot retrieves relevant information from your documents and data before generating an answer, grounded in approved business information.

AI Customer Support Automation

Automate repetitive support conversations with FAQs, triage, ticket classification and escalation — with full context when a human takes over.

AI Sales Agent

Capture leads, ask qualifying questions, recommend services, book meetings, follow up and update your CRM — moving the right prospect forward.

AI Voice Agents

AI voice agents for inbound and outbound conversations in natural speech — customer service, qualification, scheduling and call routing with human escalation.

WhatsApp Chatbot Development

WhatsApp chatbot development for customer service, lead generation, order updates and qualification — built around the WhatsApp Business ecosystem.

Discord Bot Development

Custom Discord bots for community moderation, member assistance, support, notifications, role management and workflow automation.

Rules Based Chatbot Development

Structured rules based chatbots for predictable conversations — FAQs, lead qualification, routing, appointment flows and menu driven experiences.

Multi Agent Systems

Multi agent systems where a supervisor coordinates specialized agents for complex workflows — used only when the additional complexity creates real value.

AI Agent Monitoring and Optimization

Conversation monitoring, accuracy evaluation, knowledge updates, guardrail updates and ongoing optimization so your agent improves after launch.
Clarity

Chatbot or AI agent?

The terms are often used interchangeably. They should not be. A chatbot primarily resolves the conversation. An AI agent can resolve the problem — it reasons about context, acts across your systems, and closes the loop.

GoalAI AGENTreads · decides · actsCRM & ERP readKnowledge readTools / APIs writeActiontaken ✓

Resolves the problem. An AI agent can understand context, make decisions, use tools and take actions across connected systems — lead qualification, onboarding, CRM updates and multi step workflows.

QuestionChatbotreads onlyKnowledge basereadAnswer

Resolves the conversation. An AI chatbot understands questions, maintains conversational context and provides answers from your knowledge and business data — FAQs, product information, support and low risk requests.

AI chatbot vs AI agent — how they differ at a glance.
 AI ChatbotAI Agent
What it doesUnderstands and answers from your knowledgeUnderstands, decides, uses tools and acts
ScopeSingle-step, conversationalMulti-step, cross-system, goal-driven
Touches your systemsRead-only (knowledge base)Reads and writes (CRM, ERP, APIs)
Best forFAQs, lookups, product and policy questionsOnboarding, qualification, triage, workflows
Typical buildFaster to deliverMore architecture and governance
Run-cost & governanceLowerHigher — needs real guardrails
The simple rule — if the work only needs an answer

If the work only needs an answer, a chatbot may be the smarter investment — cheaper to build and run, and faster to ship.

If it spans systems or needs follow-through

If the work requires the system to read, decide and act across multiple systems, an AI agent may be the better solution. We will tell you which one you actually need.

Get a Free Chatbot versus Agent Assessment
Two ways to start

Two ways to start — build a new AI chatbot or agent, or rescue an existing one

Every AI project usually begins in one of two places. You are building something new. Or you already built something that is not working properly.

IMG 01 · BUILD · 16:10
Founder starting fresh with a blank screen for a new AI agentFounder starting fresh at a clean desk, a blank screen ready for a new agent
Build new

Build a new AI chatbot or agent

You have identified a workflow but have no production system yet. We start with discovery and determine what should be automated, whether you need a chatbot or agent, what information and systems it needs, what level of autonomy is appropriate and how success should be measured.

  • Scoped to a clear outcome
  • Integrated into your stack
  • Designed and built around your requirements
Build a New AI System
IMG 02 · RESCUE · 16:10
Engineer fixing a stalled chatbot to production qualityEngineer reviving a stalled chatbot, screen showing a fixed, working conversation
Rescue & re-automate

Rescue an existing chatbot or agent

Your chatbot may already exist but gives inconsistent answers, hallucinates, has outdated information, cannot connect to your systems or was built as a demo but never reached production. We audit the existing system and determine what needs to change.

  • Architecture and knowledge audit
  • RAG, integration and guardrail repair
  • Rebuild where necessary — not always from scratch
Audit My Existing Bot

You do not always need to start again. Sometimes the right solution is to fix the architecture underneath what you already have — each door implies its own starting audit, but it is one expertise expressed two ways.

How we build

How we build AI systems that actually ship

Our process is designed to discover failure modes before customers do. Every stage has a gate — nothing reaches production that cannot be measured, governed and improved.

IMG 03 · PROCESS · 3:2Engineering team mapping an AI agent decision flow
Engineering team at a whiteboard mapping an agent's decision flow, sticky notes and diagrams
  1. 1

    Free AI audit and discovery

    ~1–2 weeks

    We map the workflow, define the desired outcome and determine whether a chatbot, agent or another automation approach is actually appropriate — based on the use case rather than AI hype.

    Decision gate: build, buy, partner or do nothing
  2. 2

    Architecture and scope

    ~1–2 weeks

    We define model selection, knowledge architecture, integrations, conversation design, user experience, security requirements, governance, human handoff and success metrics — you know what is being built before development begins.

    Gate: signed-off architecture
  3. 3

    Design and build

    ~3–10+ weeks

    We develop the conversational experience, retrieval system, integrations, tools, prompts and guardrails. Development happens in a controlled environment before the system interacts with live business data.

    Gate: sandbox before live data
  4. 4

    Evaluate and harden

    ongoing through build

    We test against realistic conversations and edge cases — accuracy, hallucination resistance, prompt injection, permission boundaries, incorrect requests, unexpected inputs, integration failures, human escalation and response quality.

    Gate: must clear accuracy thresholds
  5. 5

    Phased launch

    ~1–3 weeks

    We do not recommend switching on a complex AI system everywhere at once. A controlled pilot lets us observe actual usage, measure performance and make improvements before expanding.

    Gate: expand only on measured results
  6. 6

    Optimize and support

    ongoing

    AI systems need ongoing attention. We can monitor performance, update knowledge, improve conversations, optimize cost and adapt the system as your business changes.

    Gate: tuned to a live run-rate

You see a live pilot early rather than waiting for a big-bang launch, and you can switch the agent off cleanly at any gate.

Get a Quote
Our stack

Built with the right technology for the problem

We do not force every project onto one AI model or one framework. The architecture depends on what your business actually needs — latency, accuracy, compliance and budget. Hover or tap a layer for detail.

We can work across modern large language models including GPT, Claude and Gemini. The appropriate model depends on reasoning requirements, response quality, latency, safety behavior and operating cost.

Depending on the workflow, architecture may involve LangGraph, CrewAI, OpenAI SDK, Claude SDK, Microsoft Agent Framework or Google ADK. The goal is not the most fashionable framework — it is the architecture that makes the system reliable and maintainable.

RAG systems, vector databases, embeddings and governed memory help the AI work from your business information — retrieving relevant content at conversation time rather than relying entirely on general model knowledge.

Custom APIs and open integration standards connect the AI system with your CRM, ERP, helpdesk, ecommerce platform, databases and business APIs — so it does not become another isolated application.

Low-latency speech-to-text and text-to-speech for natural inbound and outbound voice agents — customer service, qualification, scheduling and call routing with human escalation when needed.

Eval harnesses, accuracy testing, red-teaming and monitoring so quality is measured before launch and observed after — the system is evaluated against defined requirements, not assumed to work.

Orchestration, a supervisor coordinating specialist agents
Supervisorroutes & coordinatesSupport agenttickets · refundsSales agentqualify · bookOps agentback-office tasksshared memory · governed hand-offs (A2A)

We never claim a certification, partner tier, or capability we don't hold. Specific tiers are marked with an asterisk until confirmed by 10turtle.

Get a Quote
AI support team and live production dashboardA support team calm at their desks while an AI agent quietly clears the queue on screen, a real production moment
In production

Grounded in your business knowledge, connected to the systems you already use

A chatbot that knows general information about the world is not necessarily useful to your business. We build retrieval based knowledge systems around your approved documents and connect to CRM, ERP, helpdesk and APIs — read only where appropriate, read and write where approved, with human approval for sensitive actions.

Get a Quote
Governance

AI governance from day one

The more an AI system can do, the more carefully it needs to be governed. A simple FAQ chatbot and an agent that can modify customer records should not have the same permissions. The objective is controlled autonomy, not unrestricted autonomy.

We don't apply one blunt policy to every agent. A read-only FAQ bot and an agent that can issue refunds get very different controls — scoped access, human approval, audit trails, accuracy testing, guardrails, escalation and circuit breakers matched to the risk of the task.

  • Scoped access — each system receives only the permissions it needs.
  • Human approval — sensitive or high impact actions can require human confirmation.
  • Audit trails — important activity can be recorded for review.
  • Accuracy testing — the system is evaluated against defined requirements before launch.
  • Guardrails — the AI has boundaries around what it can answer and what it can do.
  • Escalation — when confidence or authority is insufficient, the system hands the conversation to a human.
  • Circuit breakers — automated controls can stop actions when defined thresholds are exceeded.

The level of autonomy should match the risk of the task — read only access where the AI retrieves information without changing systems, read and write where it performs approved actions, and human approval where sensitive decisions require review before execution.

Get a Quote
Cost & timeline

What does AI chatbot development cost in Dubai?

The investment depends on what the chatbot needs to know, where it needs to operate and what it needs to do. We scope the actual system before providing an investment estimate — against a defined outcome, not a generic price list.

Qualitative tiers to help you understand scope — not 10turtle's quoted prices.*
TypeTypical build (industry range)Typical timeline
A simple knowledge chatbotFocused chatbot grounded in a defined knowledge baseGenerally less complex — faster to deliver
A connected AI assistantCRM, helpdesk, database and API integrationsMore architecture and testing required
An autonomous AI agentReasoning, decisions and actions with governance and monitoringLonger — evaluation and guardrails essential
A multi agent systemMultiple coordinated agents with orchestration complexityLongest — additional testing and coordination
How long does it take?A focused chatbot can be delivered much faster than a complex AI agent connected to several business systems. Timeline depends on scope, content readiness, integration complexity, channels, knowledge architecture, testing and governance requirements.
Realistic planningRather than promise an arbitrary delivery date, we define the scope first and provide a realistic implementation plan — so you decide with clarity, not guesswork.
Scoped before you commitProduction-grade where it matters, integrated into your stack, governed and fully owned by you — with the run-rate understood from day one.

The upside is real, too. A well-built conversational AI system can deflect repetitive support, qualify leads around the clock and give your team more capacity for conversations that genuinely require human attention — across website, WhatsApp and other channels.

Request an AI Build Assessment
IMG 09 · WHY · 4:310turtle AI team collaborating with a client
A senior engineer and a client side by side at one screen, calm and in control
One roofOne accountable partner. One roadmap. One team responsible for the outcome.
Why 10turtle

What makes 10turtle different

You do not need to coordinate a chatbot developer, automation consultant, integration developer and AI specialist separately. 10turtle brings those capabilities together under one accountable partner.

01

Not every problem needs an autonomous agent. If a rules based chatbot is enough, we will say so. If a RAG chatbot solves the problem, we will not sell you unnecessary complexity. If automation is more appropriate than conversation, we will recommend that instead. The right solution is the one that solves the business problem.

02

You get a dedicated AI engineering team — architecture, models, agents, RAG and integrations — backed by one accountable partner under one roof. No outsourcing, no white-label markup, no finger-pointing.

03

Our process is designed to discover failure modes before customers do. We measure success before we build, and we don't call it done until the system is live, governed and holding in production.

04

The agent, the prompts, the integrations and the data are yours. We build your capability, not a dependency on us.

05

When your AI system needs a home on a fast website, workflows that connect to the wider business, or a voice and personality on brand — the same team can deliver it. AI engineering, automation, web and branding and creative, one accountable partner.

Get a Quote
Selected work

Selected AI agent & chatbot work

Representative engagements across support, sales, voice, knowledge, and rescue. Real client names and verified results publish with each live case study.

What clients say

What clients say

In their words, image, audio, and video. Real, permissioned testimonials replace these before launch.

Platforms we build on

Peer partnerships across the platforms we build on

We build on Anthropic’s models as a partner, not a dependency — never under or through Anthropic.

Standards we build to

Security & Compliance Standards

ISO 27001 Certified
SOC 2 Type 2
PCI DSS Compliance
GDPR Compliance
CCPA Compliance
ISO 27018 Certified

“We follow the principles of GDPR, CCPA, and ISO standards certified to ensure security, privacy, and compliance across all operations.”

One roof

One accountable partner for the whole experience

An AI system rarely lives alone. 10turtle brings AI engineering, automation, web and branding and creative together — one accountable partner, one roadmap, one team responsible for the outcome.

FAQ

Frequently asked questions

The investment depends on what the chatbot needs to know, where it needs to operate and what it needs to do. A simple knowledge chatbot A focused chatbot grounded in a defined knowledge base is generally less complex than a system connected to multiple business systems. A connected AI assistant CRM, helpdesk, database and API integrations add architecture and testing requirements. An autonomous AI agent Agents that can reason, make decisions and execute actions require additional governance, evaluation and monitoring. A multi agent system Multiple coordinated agents introduce additional orchestration and testing complexity. The main cost factors Number of use cases Knowledge base size Data quality AI model requirements RAG architecture Number of integrations Number of channels User volume Level of autonomy Security requirements Testing requirements Ongoing monitoring We scope the actual system before providing an investment estimate. Request an AI Build Assessment

A focused chatbot can be delivered much faster than a complex AI agent connected to several business systems. The timeline depends on: Scope Content readiness Integration complexity Number of channels Knowledge architecture Testing requirements Governance requirements Rather than promise an arbitrary delivery date, we define the scope first and provide a realistic implementation plan. Frequently asked questions

An AI chatbot primarily understands and answers questions. An AI agent can understand a goal, reason about context, use tools and perform actions across connected systems. If your requirement is mainly knowledge and conversation, a chatbot may be enough. If the system needs to perform multi step work, an agent may be more appropriate.

If your customers ask predictable questions and you want complete control over every response, a rules based chatbot may be enough. If customers ask open ended questions and need natural language understanding, an AI chatbot is likely a better fit.

RAG stands for retrieval augmented generation. The chatbot retrieves relevant information from your own content before generating its response. This helps it answer from your business information rather than relying only on general model knowledge.

Yes. Depending on the CRM and use case, the chatbot can retrieve information, create or update records and support workflows through appropriate integrations.

Yes. ERP integration can allow the AI system to retrieve approved business information or perform defined actions where appropriate.

Yes. We can build WhatsApp based conversational experiences around appropriate Business API capabilities and messaging requirements.

Yes. Where appropriate, we can build a shared conversational core and deploy it across multiple channels. Channel specific requirements still need to be configured individually.

Yes. Human escalation should be part of the design rather than an afterthought. The handoff can include relevant conversation context so the customer does not have to repeat the entire interaction.

Yes. RAG architecture can connect the system to approved documents and knowledge sources.

Yes. The appropriate language architecture depends on the channels, model and content requirements. We can design conversational experiences for multiple languages and regional audiences.

Security depends on the architecture and the type of data involved. Appropriate controls can include access permissions, data handling rules, authentication, logging, human approval and system specific guardrails.

Yes. We can audit existing chatbots and agents to identify issues with architecture, prompts, knowledge, integrations, guardrails and performance.

Yes. Ongoing services can include monitoring, evaluation, knowledge updates, optimization, model changes, integration maintenance and continued development. Find out what your AI system should actually do Bring us a workflow. Bring us a chatbot that is not working. Bring us a customer support problem. Or simply bring us the idea you are not sure is worth building. We will map the use case, determine whether you need a chatbot, agent or another solution, and tell you what it would take to build properly. No unnecessary AI complexity. No chatbot for the sake of having a chatbot. Just a system designed to solve the problem. Start Your Free AI Audit See the AI Work

Team collaboration in final AI agent strategy discussionFINAL-CTA-BAND · 21:9
Let's talk

Find out what your AI system should actually do

Bring us a workflow, a chatbot that is not working, a customer support problem, or simply the idea you are not sure is worth building. We will map the use case, determine whether you need a chatbot, agent or another solution, and tell you what it would take to build properly. No unnecessary AI complexity. No chatbot for the sake of having a chatbot.

A dedicated AI team · one accountable partner.