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AI & GenAI

AI ENGINEERED TO RUN IN PRODUCTION

We deliver AI systems that survive real enterprise environments: architecture-led, governed, and multi-tech.

Enterprises don’t need more prototypes. They need AI that fits their environment, handles their real data conditions, and runs with reliability. They need AI that works inside their systems, not around them.

How We Approach AI

From concepts to running systems

We implement AI around real workflows, constraints, and integration points so each solution lands cleanly in production.

Reduce risk from day one

We validate feasibility, data readiness, architectural fit, constraints, ROI, and kill-conditions early.

Built for teams to own

We design for maintainability: clear interfaces, observability, versioning, documentation, and ownership boundaries.

In Practice

We build AI as part of your systems, not as isolated models. Here’s is how we approach every project.

Define the real problem

Business-first framing

  • Map decisions, data signals, and workflows.
  • Validate feasibility and ROI early.
  • Align stakeholders and success metrics.
  • Surface operational constraints before design.
AI that fits your systems

Architecture-led design

  • Data flows, contracts, lineage.
  • API and integration points.
  • Event triggers and orchestration.
  • Security, access, and environment constraints.
  • Cloud/on-prem compatibility.
Choose the right technique

Multi-tech AI methods

  • Predictive modeling.
  • Constraint optimization.
  • LLM and agentic systems.
  • Recommendation and ranking.
  • Document understanding and extraction.
  • Rule-based and heuristic logic.
  • Hybrid architectures.
Full AI systems, not models

End-to-end engineering

  • ETL, preprocessing, connectors.
  • Model serving and inference.
  • Validation and control flows.
  • Monitoring, drift, logging, lifecycle management.
  • Interfaces, APIs, orchestration.
  • CI/CD integration.
Keep control and transparency

Human-in-the-loop governance

  • Approval workflows and audit trails.
  • Conflict and exception surfacing.
  • Explainability and confidence cues.
  • Editable outputs and fallbacks.
Value early, adoption built-in

Iterative delivery

  • Quick wins that prove feasibility.
  • Continuous demos and integration testing.
  • Incremental scaling across systems.
  • Cross-team collaboration and capability building.
  • Documentation and operational handover.

How We Engineer It Differently

Built for complex, mission-critical environments

We’ve spent decades engineering inside legacy-heavy, high-scale systems where uptime, compliance, and stability matter. This shapes how we design AI: with architectural rigor, operational awareness, and a focus on reliability.

Governance and safety by design

We ensure that our AI is built with control surfaces: audit trails, approval flows, fallback, explainability cues, and monitoring.

Full-stack engineering depth

We create every layer needed for AI to run in production so that it becomes a stable part of the system.

Fast, iterative delivery with your teams

We work in short cycles with continuous demos, real environment integration, and tight alignment with client engineers.

In Action

From compliance-heavy workflows to messy data and mission-critical environments, we engineer AI systems that run reliably and deliver measurable value. Here’s how we’ve applied AI across industries like insurance, energy, food, finance, and telecom.

Software
Modernizing Invoicing Systems

We integrated advanced AI models based on Machine Learning, Optical Character Recognition, and Natural Language Processing, to automate key invoicing processes, featuring:

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  • Implemented automatic classification models that predict accounts and their parties for invoices, reducing manual input
  • Streamlined reconciliation, matching bank statements with accounting records
  • Established a feedback loop for model retraining, enhancing prediction accuracy over time
  • Deployed a generative AI-powered chatbot to provide instant assistance for invoice-related queries

> Learn more

Food
Food safety and compliance

We replaced the tedious process of manual temperature monitoring with an innovative AI-powered solution for 35,000 restaurants, featuring:

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  • A camera that attaches to a smartphone and recognizes ingredients accurately using computer vision
  • An embedded smart infrared thermometer that measures ingredient temperature
  • IoT sensors that track temperature in refrigerators
  • Analytics that provide actionable insights and activate related workflows

> Learn more

Insurance
Policy issuance digitization

We fully digitized the issuance of insurance policies, while staying compliant with regulations, by implementing a next-gen solution, featuring:​

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  • An Intelligent Document Processing (IDP) service integrated into the sales portal
  • IDP that corrects the uploaded images and extracts key information with a structured output and confidence score
  • An algorithm trained on GCC official documents and Arabic language
  • An advanced face verification service that checks the user’s identity through their device’s live camera
Health
Population health gamification

We created a solution focused on AI-driven experiences that engage people to lead a healthier life, featuring:

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  • A mobile app that generates health programs based on each individual profile
  • Daily goals initially set based on similar users’ behavior
  • Goals dynamically adapted based on the user’s behavioral patterns, keeping them always challenging yet attainable
  • Gamification tactics added to sustain behavioral change
Energy Energy
Energy efficiency

We used AI to enhance decision-making and boost efficiency for an EaaS model, featuring:​

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  • Savings prediction models after equipment upgrades, incorporating aggregate data and metrics from multiple metering data points
  • Usage prediction based on historical data and environmental factors (like weather and climate zones) to forecast energy needs accurately; this is especially useful for new sites without prior usage data, leveraging data from similar locations
  • Anomaly detection, using machine learning to identify unusual energy usage patterns
  • An LLM-powered chatbot trained on legal documents; it handles queries, processes text, images, and spreadsheets, and can pull data directly from the database

 

Telecom
Talk to your documents

We built a robust multi-agent RAG application using an advanced LLM to securely query a corporate knowledge base, featuring:

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  • An advanced language model that understands and responds to a wide range of general knowledge queries and can satisfy user commands
  • Integration with an expansive knowledge base to retrieve, understand and answer queries based on precise document information and provided resources
  • A built-in analytics agent that provides detailed insights and analytics based on the data retrieved and user interactions
  • An intuitive user interface that simplifies interaction and enhances user experience

> Learn more

A STRUCTURED WAY TO PRIORITIZE AI

Our SAIO framework helps teams identify high-value, buildable AI opportunities, validate feasibility early, and design the supporting architecture before model work begins. It reduces delivery risk and creates a clear path from idea to a system that runs.

Download The Framework

Insights

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AI

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AI’s New Rules for CIOs – Recap from Gartner CIO Dubai

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Walking Through AI Disruption With A Blindfold

NEXT CAPABILITY

Data & Analytics

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Let’s Reimagine Together!

Take a leap into the future, harness the power of innovation and accelerate your transformation to unlock new opportunities.

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