Private AI & LLM Infrastructure

Custom AI Development & Machine Learning

Not every problem needs a large language model. AICubes builds custom machine learning systems — forecasting, anomaly detection, classification, ranking and optimisation — trained on your own operational data and engineered to run reliably in production.

We handle the full lifecycle: data preparation, feature engineering, model training and evaluation, deployment behind APIs, and monitoring for drift once the model is live.

01Private AI & LLM Infrastructure

What we deliver

  • 01

    Use-case scoping

    We define the decision the model supports, the metric that matters and the data available before any training starts.

  • 02

    Forecasting

    Demand, revenue, workload and capacity forecasts with explainable drivers.

  • 03

    Anomaly and fraud detection

    Models that flag unusual transactions, readings or behaviour for human review.

  • 04

    Classification and routing

    Automatic categorisation of requests, documents and cases in Arabic and English.

  • 05

    Model fine-tuning

    Adapting open-weight language and vision models to your domain with your data.

  • 06

    MLOps

    Versioned pipelines, automated retraining, evaluation and drift monitoring.

02Private AI & LLM Infrastructure

Typical use cases

  • Demand and inventory forecasting for retail and distribution
  • Predictive maintenance for equipment and fleets
  • Fraud and anomaly detection in financial transactions
  • Automatic routing of citizen requests and complaints
  • Pricing and resource optimisation
03Private AI & LLM Infrastructure

How we deliver

  • On-premise, private cloud or hybrid

    Deployed where your data is allowed to live — your data centre, an in-country cloud, or a mix.

  • Arabic and English

    Interfaces, models and documentation designed for bilingual users from the start.

  • Integrated with your systems

    Connected to existing databases, identity providers, ERPs and line-of-business applications.

  • Supported after launch

    Monitoring, model updates and a named engineering contact once the system is live.

Frequently asked questions

It depends on the problem. We start with a short data assessment and tell you plainly whether the available data can support a reliable model — and what to collect if it cannot.

You do. Models trained on your data, and the code that produces them, are delivered to you as part of the engagement.

Plan your next AI system with an engineer.

Tell us what you need to build. We respond within one business day with next steps, questions and — where the scope is clear — an indicative quote.