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Service · Automation

AI agents for
daily operations.

Agents that work inside WhatsApp, your CRM and your admin panel. They read live business data and complete the small repetitive tasks your team does all day.

WhatsAppMulti-LLMCRM intelligenceDocument AIWorkflows
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AI Agents & Automation
ZaadCore service
WhatsApp agents
Operations lookups
Document drafting
Lead qualification
CRM intelligence
Document extraction
Scoped before it is quoted Dubai
Models
OpenAI · Gemini · Claude
Channel
WhatsApp & in-app
Data
Connected & live
Actions
Reviewed, not auto-sent
Connected to live data

The agent queries your stock, invoices and customer records at the moment it is asked. It never answers from a stale export.

It drafts, a human sends

Agents prepare the purchase order, reply or quote for a person to approve. Anything touching money or customers needs explicit confirmation by design, not as a setting.

Model-independent by default

We build against OpenAI, Gemini and Claude behind one interface, so switching provider after a price rise, an outage or a better model is a configuration change rather than a rewrite.

An agent at work

It answers from live data,
then waits for approval.

The agent reads the live stock figure and drafts the purchase order. A person approves before anything reaches the supplier.

Awaiting approval

What agents
take off your team.

Each agent starts with one well-defined job and widens once it is trusted.

WhatsApp agents

On the WhatsApp Business API. Answers customer and staff questions, captures orders and enquiries, escalates to a human with the full thread attached.

Operations lookups

Stock levels, order status, pricing and delivery dates answered from live systems in plain language.

Document drafting

Quotes, purchase orders, offer letters and reports drafted from real records and queued for approval, with the source data cited.

Lead qualification

Inbound enquiries scored and routed, with a first reply drafted for the rep. Stale leads resurface before they go cold.

CRM intelligence

Thread summarisation, next-best-action on open deals, and ticket triage with a drafted first response, labelled as AI-generated.

Document extraction

Invoices, delivery notes and statements read into structured records, with low-confidence fields flagged for a human.

Workflow automation

Scheduled checks, escalations, reminders and multi-step routines that run on their own.

Privacy & guardrails

Feature masking keeps names and contact details from the model, per-role scoping limits what an agent reads, and every action is logged in full.

How we get
an agent live.

We start with one job, done reliably, before widening the scope.

  1. 01
    Pick the job

    We pick a high-volume, low-judgement, well-defined task: a question your team answers twenty times a day.

  2. 02
    Connect the data

    Read-only access to the systems holding the answer, with masking and role scoping agreed first.

  3. 03
    Pilot with a human in the loop

    The agent drafts and your team approves. How often the draft is used unchanged decides when to widen.

  4. 04
    Widen carefully

    Once it is trusted, we extend scope or add actions. Each new capability goes through the same pilot.

Agents are built on your existing systems. If the data is not queryable yet, that groundwork sits in the Build or Integrations scope.

What you should
expect from it.

Automation pays off where the work is repetitive and the answer is checkable.

We work in
OpenAIGeminiClaudeWhatsApp Business APINode.jsPostgreSQLWebhooks
Faster first response

Customers and staff get an answer immediately instead of waiting for the one person who knows.

Fewer interruptions

Routine lookups stop landing on the warehouse, finance and sales teams as messages.

Consistent documents

Quotes and orders drafted from the same source data in the same format every time.

Work outside hours

Enquiries captured and triaged overnight, ready for the team in the morning.

An audit trail

Every agent action logged and attributable, including the data it read.

No model lock-in

Provider chosen per task on cost and quality, and changeable without a rebuild.

Questions

Before you
get in touch.

Will the AI make things up?

It can. We ground agents in your live data, cite the records used, and keep a person between the draft and the customer. Tasks that cannot be checked are not automated.

Does our data get used to train a model?

No. We use business API tiers that exclude your data from training, and mask identifying fields the task does not need.

Which model do you use?

Whichever fits the task on quality and cost. One interface across OpenAI, Gemini and Claude keeps the choice reversible.

Do we need the WhatsApp Business API?

For a WhatsApp agent, yes, and we handle setup and number verification as part of the project. Agents can also live inside your own app or CRM.

Talk to us

Not sure which product
fits your operation?

Tell us where your team is losing time. We’ll show you how ZaadCore can simplify the workflow — with a ready-to-use platform or a solution configured around your business.