Applied Agent Engineering
Python, approved LLM APIs, RAG, document ingestion, embeddings, vector search, enterprise knowledge systems, agent workflows and deployment.
A practical Phase 0 execution node designed to turn national AI ambition into trained engineers, locally deployable AI systems and commercial startup prototypes.
The proposal is simple: establish a small, operational AI factory inside the IT Park ecosystem before larger national-scale compute comes fully online. The node would combine local NVIDIA-class compute, hands-on engineering training, startup production and controlled sovereign AI workloads.
The objective is to create a controlled environment where engineers and startups learn by building real systems on the same class of local AI infrastructure they may later operate at larger scale.
| Primary engineering node | NVIDIA DGX Station, powered by the GB300 Grace Blackwell Ultra Desktop Superchip. Intended for advanced local inference, model development, fine-tuning, agents and data-science workloads. |
|---|---|
| Developer / startup node | NVIDIA DGX Spark. Intended for prototyping, local inference and practical fine-tuning workflows, including parameter-efficient methods. |
| Operating principle | Local execution by default for sensitive or policy-restricted data; cloud and external APIs used only where permitted and useful. |
| Procurement approach | Jointly explore strategic hardware contribution, evaluation allocation, preferential procurement, co-funded deployment or another mechanism acceptable to NVIDIA and IT Park. No assumption of free hardware. |
Final hardware, software, licensing and delivery are subject to vendor availability, export controls, local procurement rules and separate agreements.
Python, approved LLM APIs, RAG, document ingestion, embeddings, vector search, enterprise knowledge systems, agent workflows and deployment.
Local inference, 3B–9B model workflows, LoRA / QLoRA / SFT, synthetic datasets, evaluation, optimization, Jupyter and the NVIDIA software stack.
Every team exits with an auditable artifact: a working agent, RAG application, fine-tuned model, enterprise proof of concept or commercial prototype.
Initial cohort of 20–50 engineers, founders and startup teams trained through practical engineering tasks and deployment work.
A portfolio of working AI agents, RAG systems, local model workflows and sector-specific prototypes suitable for technical review.
Selection of controlled government, enterprise, education or industry pilots where local AI execution provides a clear data-governance or operational benefit.
An operating playbook, training baseline and application pipeline that can inform future expansion into larger national AI infrastructure.
Institutional host; nominate a project owner; provide the local programme environment, participant access and coordination; support alignment with relevant Ministry and national AI initiatives.
Provide programme architecture, engineering curriculum, mentor enablement, deployment methodology, local-AI/RAG/agent workflows, evaluation standards and commercialization structure.
Subject to separate NVIDIA approval: explore technology infrastructure participation, technical enablement, appropriate software access and DLI alignment. NVIDIA participation is not represented as agreed or guaranteed by this proposal.
GENCITY is supported by affiliated companies under common management across the United States, United Kingdom and United Arab Emirates.
Delaware, United States. Operator of the GENCITY platform and AI infrastructure / applied engineering arm. HYBT Technologies, Inc. is an NVIDIA Inception member and an AI for Good initiative participant.
Programme participation is presented as an organisational credential and does not imply endorsement, sponsorship or approval of this proposal.
England & Wales · Company No. 16665302. UK software, web-portal and education company; owner of the registered GENCITY® trade mark and the group’s UK intellectual-property base.
Umm Al Quwain, United Arab Emirates. UAE education, EdTech and innovation activity, including participation in the Ras Al Khaimah Teachers Network (RAKTN), which is managed by the Sheikh Saud bin Saqr Al Qasimi Foundation for Policy Research.
The proposal is intentionally aligned with publicly stated initiatives rather than presented as a new national policy.
For IT Park Uzbekistan, Ministry, university or institutional stakeholders who want to evaluate the Phase 0 model, the next step is a focused scoping discussion covering host environment, cohort, use cases, governance and technology engagement.
Open institutional enquiry