Custom Software
AI that works inside the systems you already run
Your team already has an ERP, a CRM, spreadsheets and a support inbox. We connect AI to that stack directly, so it reads your real data, follows your real approval steps and writes back where your team already looks.
2 to 4
weeks to a working first integration
2
languages supported from day one, Arabic and English
24/7
monitoring once the integration is live
The direct answer
This is the work of connecting AI to systems you already use, not replacing them. We build the middleware, prompts and data pipelines that let an AI model read from your ERP or CRM, act on real records and write results back safely. It suits Saudi companies with an existing system of record who want AI to speed up a specific workflow (quoting, reconciliation, support triage, document review) without a platform rebuild.
What this removes.
Data trapped in silos
Today
Your ERP, CRM and spreadsheets don't talk to each other, so someone re-types the same number three times.
With the system
One integration layer reads and writes across systems, so a number entered once shows up everywhere it needs to.
AI tools that don't know your business
Today
Generic AI chat tools give generic answers because they've never seen your pricing, your customers or your stock levels.
With the system
The AI is connected to your live data, so answers reflect actual inventory, actual prices and actual customer history.
Arabic documents nobody automates
Today
Invoices, PO's and contracts arrive in Arabic PDFs and someone keys them into the system by hand.
With the system
Documents are parsed automatically in Arabic and English, with the extracted fields dropped straight into your system.
No visibility once it's live
Today
Past automation attempts broke quietly and nobody noticed until a customer complained.
With the system
You get logs, error alerts and a monthly accuracy check, so a failure gets caught before a customer sees it.
What lands in your hands.
Integration middleware
The API or service layer connecting your existing system to the AI model.
Document and data extraction
Parsing invoices, PO's, contracts and forms in Arabic and English.
Workflow automation
Rules and triggers that move a task through approval without manual re-entry.
Write-back to your system of record
Results land inside your ERP or CRM, not a separate dashboard nobody opens.
Monitoring and error handling
Alerts when an integration fails, plus a fallback to manual review.
Admin controls
Screens for your team to review, correct or override what the AI produced.
Systems and platforms we work with
- App Store
- Google Play
- Apple
- Android
- iOS
- macOS
- Windows
- Web
Systems and platforms we work with
- React
- Next.js
- TypeScript
- Node.js
- Python
- Flutter
- PostgreSQL
- Supabase
- Tailwind CSS
- Docker
- GitHub
- Google Cloud
- Figma
Five stages. You sign off every one.
Read each stage as a small contract: what we need from you, what lands in your hands, and the sentence that has to be true before we move on.
- System audit3 to 5 days
- Pipeline build1 to 2 weeks
- Accuracy testing3 to 7 days
- Staged rollout1 to 2 weeks
- Full launch and supportongoing
System audit
3 to 5 days
We map your current system, its data structure, its API (or lack of one) and the specific workflow you want AI to speed up.
- Give access to the relevant system
- Name the one workflow to fix first
- A data and access map
- A written integration plan with scope and cost
We move on when the plan names the exact data flow, the AI's role in it, and what stays manual.
Pipeline build
1 to 2 weeks
We build the connection between your system and the AI model: authentication, data pull, prompt design and the write-back path.
- Answer questions on edge cases
- Provide sample documents or records
- A working pipeline in a test environment
- Sample outputs against real data
We move on when the pipeline runs end to end on real records without manual patching.
Accuracy testing
3 to 7 days
We run the integration against a batch of real historical data and measure where it gets things right, wrong or unsure.
- Review flagged outputs
- Set the accuracy bar you need
- An accuracy report by field or task type
- Fixes to prompts or rules where accuracy fell short
We move on when accuracy on the test batch clears the bar you set, in writing.
Staged rollout
1 to 2 weeks
We turn the integration on for a limited slice of real traffic first, with a human checking outputs before full rollout.
- Assign a reviewer for the pilot window
- Flag anything that looks wrong
- A live pilot on a subset of records
- Adjustments based on real usage
We move on when the pilot runs a full week with no unreviewed errors reaching your customers or your books.
Full launch and support
ongoing
The integration runs on all relevant records with monitoring in place, and we stay on for fixes and tuning as your data changes.
- Report anything unusual
- Tell us when your source system changes
- Uptime and accuracy monitoring
- A monthly check-in on performance and drift
We move on when this stage doesn't end, it's the standing support arrangement.
Asked before signing.
How do you price an AI integration project?
By scope, not by hours billed blind. After the system audit we quote a fixed price for the integration based on the number of data sources, document types and workflow steps involved. Ongoing monitoring and tuning after launch is a separate monthly fee, agreed upfront, not added later.
Can this work with an old or custom-built system that has no proper API?
Often yes. We've built integrations against systems that only export CSV files or have a limited legacy API. It takes longer and the audit stage tells you honestly if your system is too closed to connect safely. We won't promise an integration that isn't realistic.
Does the AI read and write in Arabic?
Yes, both extraction and any generated text handle Arabic and English from the start, since that's the reality of Saudi business documents. We test on real Arabic invoices, contracts and correspondence during the accuracy testing stage, not just English samples.
What happens to our data, and does this comply with PDPL?
Your data stays within the integration you approve, we don't use it to train external models, and access controls follow PDPL requirements around consent and data minimization. We document exactly what data moves where in the integration plan before any build starts, so your legal team can review it.
Get AI working inside your systems, not next to them
Tell us what system you run and what workflow is slowest today. We'll tell you honestly whether an integration makes sense and what it would take.