// AI EMPLOYEES · BUILT + RUNEN · AR

AI employees that do real work in your business

Clouds is an AI agent development company that designs, builds, and runs agents doing real work: answering and qualifying leads, serving customers in Arabic and English, and running back-office workflows end to end. Every agent operates within limits you set, with a human approving the decisions that matter, and everything it does is logged and auditable.

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// MEET THE AI EMPLOYEES

Meet the AI employees. Hire one this month.

An agent in a demo is a toy. An agent with a job description is an employee. These are the six roles Clouds builds, deploys, and runs for businesses across Lebanon and the GCC: each one scoped to real work, fluent in Arabic, English, and French, acting within limits you set, with a human approving the decisions that matter and every action logged. Pick the role that hurts most. That is where an engagement starts.

// CUSTOMER SUPPORT · AR EN FR

Nour, the Customer Support Employee

Every customer answered in their own language, at any hour, with the hard cases handed to your team instead of dropped.

Converses in Arabic, English, French, and the code-switched mix customers in this region actually write, on your site, on WhatsApp, and over email.
Answers from your real documents, policies, and catalog through retrieval, so responses are grounded in your content, not a model's imagination.
Books, tracks, and escalates within limits you set: sensitive cases wait for a human, and every conversation is logged and auditable.

// E-COMMERCE · STOREFRONT OPS

Zain, the E-Commerce Employee

A storefront that answers, follows up, and closes while your team sleeps.

Answers product, stock, and delivery questions straight from your live catalog, in the language the shopper writes in.
Runs cart and checkout follow-up over WhatsApp and email, including cash-on-delivery confirmations on the rails Lebanese checkouts actually use.
Keeps order-status conversations off your team's plate, with refunds and exceptions gated behind human approval.

// SALES · SPEED TO LEAD

Sami, the Sales & BizDev Employee

No lead waits for Monday. Every enquiry answered, qualified, and booked in minutes.

Responds to new enquiries across your site, WhatsApp, and email the moment they land, in Arabic or English.
Qualifies and scores each lead against your criteria, routes it into your CRM, and notifies the right person.
Drafts follow-ups and proposal outlines for your team to approve and send, so the pipeline moves without anyone remembering to push it.

// MARKETING · ALWAYS-ON CONTENT OPS

Maya, the Marketing & Social Employee

A content operation that ships every week, in both languages, without hiring a content team.

Drafts campaign copy, social posts, and email sequences from your brand system, authored per locale rather than translated.
Keeps a content calendar moving: drafts queued, variants prepared, and everything held for your approval before it publishes.
Reports what ran and how it performed into one dashboard, so the next month's plan starts from data, not memory.

// FINANCE · BACK-OFFICE

Karim, the Finance & Back-office Employee

Invoices out on time, reminders sent, documents chased, and nothing money-moving happens without a human.

Generates invoices and payment reminders on schedule and chases the documents that stall your month-end.
Keeps records consistent across the tools you already run, syncing CRM, sheets, and accounting so no one re-types anything.
Holds every payment-adjacent action behind an approval gate, with a full audit trail of what was sent, when, and by whose sign-off.

// OUTCOMES, NOT DEMOS

What an AI agent does for a business

Forget the technology for a second and look at the outcomes. A lead that messages your site on Friday night gets answered, qualified, and booked in minutes instead of waiting for Monday, when it has already gone to a competitor. A support queue that used to eat two people's days gets absorbed, in Arabic and English, with the hard cases escalated to a human. A workflow that crossed three tools and someone's memory now runs itself, and leaves an audit trail.

That is what an agent is: software that plans, decides, and executes multi-step work, instead of just answering questions. And a single agent is only the start. When agents coordinate across sales, operations, and support on one company's real data, that is part of a larger pattern we call the agentic operating system (the coordinated AI workforce that runs Clouds itself), and it is what we actually sell.

// FOUR FAMILIES

Agents we build

Lead response and qualification.

Capture, qualify, route, and follow up on demand across your site, WhatsApp, email, and CRM, so no lead leaks after the click.

Conversational support.

Context-aware assistants that answer, book, and act in Arabic, English, and the code-switched mix real customers in this region actually write. Grounded in your own documents and policies, not hallucinated.

Content and commerce operations.

Agents that generate product content, keep catalogs and campaigns moving, and scale output without scaling headcount.

Internal workflow agents.

The unglamorous wins: chasing documents, drafting follow-ups, moving approvals, syncing systems. This is the deepest overlap with our automation pillar, and when the agent needs to live inside a product, it becomes an app development engagement.

// GOVERNANCE = RISK REDUCTION

Human approval gates, by design

An agent that can act on your business is only an asset if you control what it can do, so governance is engineered in from the first design, not bolted on for the audit. Agents act within limits you set, and high-stakes steps wait for a person. Answers are grounded in your real content through retrieval and guardrails, not left to a model's imagination. Your data stays yours: access tightly scoped, PII controlled, nothing used to train public models. And everything, code, prompts, models, infrastructure, hands over to you at the end.

For the buyer this is not compliance decoration. It is the difference between an agent you can put in front of customers and auditors, and a demo you quietly turn off after the first bad answer.

// PROOF · LIVE SYSTEMS

Proven in production

We are building a quote and bind application for the GCC insurance market right now: instant quotes, comparison, document capture, payment, and policy issue, mobile-first, in English and Arabic, with approval gates exactly where an insurer's judgment still matters.

And the deepest verified proof: Unlock Blockchain runs 41 AI endpoints in production inside its publishing platform, AI embedded across a real editorial pipeline rather than demonstrated in a slide deck.

Our own business is the third proof. Our acquisition, lead handling, and proposals run on the same agentic systems we sell. We use what we sell.

// DISCOVERY → PRODUCTION

How an engagement runs

We do not run year-long AI programs that never ship. Discovery maps the workflow and the revenue case, then scope, price, and timeline are fixed and signed before code. You see a working build in weekly demos, the agent goes to production in weeks rather than quarters, and after launch we watch for drift and keep it improving so it does not quietly rot.

// FAQ

FAQ

What is the difference between a chatbot and an AI agent?

A chatbot answers questions; the actual work still lands on a human. An AI agent plans, decides, and executes multi-step work: it can qualify the lead, book the meeting, chase the document, and update the CRM, with a human approving the sensitive steps. The practical test is simple: after the conversation ends, did the work happen, or did someone on your team still have to do it?

Can agents work in Arabic?

Yes, natively. Our agents converse in Arabic, English, and the code-switched mix customers in Lebanon and the GCC actually write, because the region's messages rarely stay in one language. Arabic capability is designed in from the start, not translated in afterward, and it is already live in production systems.

What does an AI agent development engagement cost?

We price by scope, not by hour, so the honest answer starts with your workflow. Discovery identifies the work the agent will take over and the revenue or hours it recovers, then you get a fixed scope, price, and timeline to sign before any code is written. The fastest path to a real number is to start the brief.

How do you keep an agent from making mistakes?

Three layers. Grounding: answers are tied to your real documents, catalog, and policies through retrieval, not generated from thin air. Limits: the agent acts inside boundaries you set, and high-stakes steps wait for human approval. Audit: everything the agent does is logged, so you can see exactly what happened and tighten the limits over time. After launch we monitor for drift and performance drops.

// LET'S MAKE RAIN

Pick the workflow that hurts most.

One Opportunity Session maps what an agent takes over first, what stays human, and what the system pays back. Fixed scope before any code.