Three phases: Advise, Implement, Operate. Anchored around a product-first delivery approach where AI runs through every engagement, not just a line on the service menu.
Most engagements start in one phase and scale across the others as the relationship proves out. We stay accountable for the outcome across all three.
Strategy, architecture, and business-case design for AI transformation. The phase that determines whether the programme succeeds, before a single line of code is written.
JumpDeploy the platform, integrate the data, deliver the AI use cases. End-to-end build on Quanterra, Azure, and bespoke solutions where required.
JumpSteady-state operations, continuous improvement, managed AI, and full IT outsourcing under clear SLAs with bilingual support.
JumpWe begin with the business question, not the technology. Advise is where we translate strategic intent into a transformation roadmap the organisation can commit to, with clear business outcomes, a defensible business case, and the architecture decisions that will carry the programme to production.
Opportunity mapping, use-case prioritisation, and an executable roadmap aligned to business value and regulatory reality.
Target-state architecture for AI, data, and integration layers, including data sovereignty, governance, and auditability from day one.
Financial modelling, benefits tracking, and programme-governance design, so the board, finance, and risk functions know exactly what they are approving.
Detailed design of specific AI use cases, tied to organisational processes and measurable business outcomes.
Platform, model, and vendor selection balanced against data sovereignty, capability, cost, and your existing technology estate.
Programme design aligned to PDPL, DESC, CBUAE, and ISO 27001 and 42001, so compliance is built in from the start rather than reviewed after the fact.
Our Advise phase isn't AI-optional. Every strategy we design, every roadmap we write, every business case we model is oriented around what AI makes newly possible, and where it is not the right answer. You don't go through GiT's Advise phase and come out with a pre-AI programme.
Implement is where the Quanterra portfolio, Microsoft AI Cloud technologies, and custom AI solutions come together. We deploy, integrate, and ship use cases under one accountable delivery team, combining product, platform, and engineering depth into a single coherent build.
Platform deployment, agent orchestration, Auto-RAG knowledge base, and governance setup for the Enterprise Agentic OS.
Risk, Contract, Conform, and Engage deployed, configured, and integrated with enterprise systems and existing processes.
Platform setup, agent design, and integration into enterprise data estates. Deployed across Azure UAE regions with sovereign-ready configurations.
Custom copilot design, deployment, and integration for employee-facing and customer-facing AI assistants.
Model engineering, MLOps, and production deployment for domain-specific machine-learning workloads.
Private foundation-model deployments with enterprise data protection and sovereignty compliance.
Domain-specific model engineering when no off-the-shelf solution fits, from concept through production deployment.
AI-driven process automation combining RPA, agentic workflows, and decision engines across the enterprise.
Forecasting, pattern detection, and decision support using enterprise data with full provenance and auditability.
Integration of AI capabilities into existing applications including ERP, CRM, HCM, and custom systems, without rip-and-replace.
PMO setup, governance, and steering for complex multi-workstream AI transformation programmes.
Organisational change management, training, and business-readiness for AI-led operational transitions.
Data pipelines, API integration, and master-data management so AI has the context it needs to perform.
Zero-trust architecture, identity management, and regulatory compliance engineered into every implementation.
Most AI engagements are custom builds that ship once and wait for the next project. Ours start with the Quanterra product, so you inherit a platform, not a one-off custom build. Custom work extends the product where needed; it doesn't replace it.
Operate is how value compounds. The AI estate evolves, models drift, regulations change, and the organisation learns. We stay embedded, fully or co-managed, with clear SLAs, continuous improvement, and bilingual service support that keeps the transformation delivering well beyond initial go-live.
End-to-end operation of the Quanterra platform and modules, including monitoring, incident response, and quarterly tuning.
Drift detection, performance monitoring, and governance for production AI models with full audit trails on every decision.
24/7 operation of Azure AI workloads (Foundry, Copilot Studio, ML Studio) under outcome-based SLAs.
Quarterly reviews and iterative improvement so your AI estate gets better every cycle, not just at upgrade time.
End-to-end IT estate management under outcome-based SLAs, for clients consolidating technology operations.
Multi-tier, bilingual Arabic/English service-desk operation with 24/7 coverage.
Day-to-day operation, patching, monitoring, and incident handling across infrastructure and cloud.
Specialist AI and engineering professionals embedded in client teams, under flexible commercial models.
24/7 security operations, SIEM operation, and managed detection and response across enterprise estates.
Ongoing alignment to PDPL, DESC, CBUAE, ISO 27001, and 42001 with continuous evidence collection and attestation.
Most of our clients begin in Advise, whether that is an AI strategy, a use-case design, or a technology selection, and move into Implement once the programme has a clear direction. Tell us where you are.
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