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AI that reads and writes your business systems, with guardrails

AI Agents inside Your ERP and CRM in Qatar

An AI agent is only useful if it can act: read the invoice and create the bill, take the WhatsApp order and raise it in the ERP, draft the reply from the customer's history and log it. We build agents that work inside Zoho, Odoo and ERPNext, with a human checkpoint where it matters.

  • Agents that read and write CRM, ERP, email and documents through governed APIs
  • Invoice and document capture, order entry, customer replies, data quality and assistants
  • Arabic and English, including Arabic documents and Gulf-dialect messages
  • Guardrails, approval checkpoints and audit trails on every action
Doha-based teamArabic and EnglishSupport after go-live

Book a free consultation

A 30-minute call, no obligation. We will tell you if we are not the right fit.

We use your details only to answer this enquiry. No lists, no resale.

Partner on four platformsZoho, Odoo, ERPNext and ManageEngine
Qatari practiceVAT, e-invoicing, GRSIA and WPS workflows
Arabic + EnglishInterface, documents and reports
Doha HQAl West Bay, working nationwide

Why we build AI agents inside business systems rather than beside them

The AI use cases that pay back in a Qatar business are unglamorous: a supplier invoice arriving by email that becomes a draft bill in Zoho Books or Odoo with the right supplier, VAT and account, waiting for approval. A WhatsApp order from a retailer that becomes a sales order with stock checked. A support message answered from the customer's contract and history, in Arabic, with a person reviewing before it goes. A weekly pass over the CRM that finds duplicates and stale deals and proposes fixes.

Each of those needs the agent to read from and write to the systems of record, safely. That is where most AI projects fail: a chatbot beside the ERP that cannot act, or an agent given direct database access that nobody can audit. We build agents on governed APIs over Zoho, Odoo and ERPNext, with scoped permissions, approval checkpoints for anything that moves money or commits the company, and a log of every action and its reasoning.

Because we implement the ERP and CRM as well, the agent is designed with the data model rather than around it. For document-heavy processes, AI document processing goes deeper; for the wider AI practice, including chatbots and voice agents, our parent company Shyphan AI Solutions covers the full range.

What we hear before an AI project

“We tried a chatbot and it could not do anything”

It answered questions from a document and never touched the system where the work happens.

“Invoices arrive by email and someone types them”

Hundreds a month, each keyed by hand, each with a chance of error.

“Orders come on WhatsApp and get missed”

Retailers message a salesperson's phone, and the order reaches the ERP hours later, or not at all.

“We are nervous about AI touching finance”

Rightly. Nobody wants an agent posting journals without a human in the loop.

Agents we build most often

Invoice and bill capture

Supplier invoices from email and WhatsApp read, matched to POs and suppliers, and created as draft bills with VAT and accounts set, awaiting approval.

Order entry from messages

WhatsApp and email orders parsed into sales orders with items, quantities and stock checked, confirmed back to the customer.

Customer reply drafting

Replies drafted from the customer's contract, invoices and history in Arabic or English, reviewed by an agent before sending.

CRM and master-data hygiene

Duplicates, missing fields and stale records found and fixes proposed for approval.

Internal assistants

Staff ask questions across CRM, ERP and documents and get answers with sources, not guesses.

Report narration

Weekly management reports summarised in plain Arabic and English with the numbers linked to the source.

How we deliver AI agents

Candidate assessment

Processes ranked by volume, error rate and value; the pilot chosen on evidence.

Baseline measurement

Time, error rate and cycle time measured before the pilot so the result is a number.

Guardrail design

Permissions, approval checkpoints, allowed actions and escalation designed with finance and IT.

Build and pilot

Agent built on governed APIs and run on real data alongside the manual process.

Monitoring and audit

Every action logged with its reasoning; exceptions routed to a person.

Scale carefully

Measured again, then extended to the next process under a plan.

AI agents for Qatar businesses

Arabic documents and messages

Arabic invoices, contracts and Gulf-dialect WhatsApp messages read correctly, and replies written in natural Arabic.

Data handling in writing

Which models and services are used, where data is processed and what is retained, documented before the pilot.

Finance stays governed

Agents create drafts; people approve anything that moves money or commits the company.

PDPPL-aware design

Personal data minimised, access scoped and logs retained according to policy.

How the engagement runs

Each stage has a real duration against it, so you can plan around it.

01

Assessment

Candidates ranked and the pilot chosen; baseline measured.

1 - 2 weeks
02

Guardrails and design

Permissions, checkpoints, prompts and integration design agreed.

1 - 2 weeks
03

Build and pilot

Agent built and run on real data alongside the manual process.

4 - 8 weeks
04

Measure and scale

Results against baseline; next process scheduled.

Ongoing

What you get

Concrete deliverables, so you can hold the proposal to something.

Assessment

  • Ranked candidate list with volumes
  • Measured baseline
  • Guardrail and data-handling design
  • Fixed-price pilot proposal

Pilot

  • Agent on governed APIs
  • Approval checkpoints and audit log
  • Arabic and English handling
  • Parallel run with the manual process

Scale

  • Measured results
  • Documentation and admin training
  • Monitoring and exception routing
  • Plan for the next process

Why businesses pick us

Partner on four platforms, not one

We are a Zoho, Odoo, ERPNext and ManageEngine partner and also implement Salesforce. If an AI agent is the wrong fit for the problem you described, we will say so before you buy licences rather than after.

Arabic and English in one system

Interface, documents and reports in both, which matters when the team works in Arabic and management reads reports in English.

Configured for Qatari practice

Invoicing workflows configurable around GTA e-invoicing, VAT treatment set at entry, and payroll outputs shaped for WPS and GRSIA.

We stay after go-live

The first month-end close surfaces everything the scoping missed. Most of the real value of an implementation is delivered in those weeks.

A team in Doha, not a ticket queue

Consultants you can meet, in your timezone and your working week, who scoped the project and then configured it.

We will tell you not to buy

If the problem is your data or your process rather than your software, a new licence will not fix it. We say that early.

Organisations we have worked with

A selection of the organisations we have delivered ERP and business software work for, across finance, healthcare, trading, logistics and professional services.

Questions before you book

It can create drafts and proposals. We design checkpoints so a person approves anything that moves money or commits the company, and every action is logged with its reasoning.

Yes. Arabic invoices, contracts and Gulf-dialect messages are handled, and replies are written in natural Arabic or English.

It depends on the models and services chosen for your pilot. We document which are used, where data is processed and what is retained before anything runs.

Zoho, Odoo, ERPNext, email, WhatsApp Business, document stores and custom systems, through governed APIs.

We measure time, error rate and cycle time before and after the pilot, and the agent runs alongside the manual process until the numbers justify switching.

It removes keying and searching. The people who did that work review exceptions and handle the cases that need judgement.

Pick one process and pilot an agent on real data

Tell us where the keying and the waiting happen. We will measure it and propose a pilot with guardrails.