For operators in Riyadh, we run custom chatgpt development projects that leave you with production systems your team can maintain, not a vendor-only black box.
We build custom chatgpt development for teams in Riyadh that need working software, not a slide deck for next quarter's steering committee. The buyers we work with in Riyadh tend to sit inside government, banking, and Vision 2030 programmes, and they want ROI they can point to at a board meeting. So our default is private ChatGPT-style systems trained on your data and deployed on your infrastructure, measured and iterated before anything touches production traffic. By the time we hand over, the system is deployed on your cloud, monitored on your dashboards, and covered by tests your engineers can read. The team is remote-friendly but in-region, so travel to Riyadh for workshops and go-live is standard, not a favour we ask for. The reason clients bring us back for the second and third custom chatgpt development project is the handover: docs, evals, runbook, and a person who picks up the phone. If you already know the outcome you want, we can scope the first release inside a week and start building the week after.
Buyers in Riyadh are done with pilots. What they want now is one production system, measured, running, and reducing a real cost line or lifting a real revenue line. That's the frame we work inside.
The private ChatGPT sits inside your cloud account or on-prem. No conversations training external models, no data leaving the perimeter you control.
Answers pull from your documents, wikis, tickets, and product content, with citations. It's a ChatGPT that actually knows your business.
Log in with your identity provider, see the documents your role is allowed to see, and nothing else. Access control matches your existing HR and Active Directory setup.
Every conversation is logged with user, timestamp, sources, and cost, so audit, security, and finance can see exactly what's happening across the tool.
A private ChatGPT trained on your policies, playbooks, and product content, available to every employee through SSO.
Sales copilots, legal review assistants, and support tools grounded on the docs the function actually cares about, not the whole company.
A private ChatGPT that meets your data-residency and audit needs, deployed in the cloud region your regulator expects.
For Riyadh clients delivering Vision 2030 mandates, we build custom ChatGPT systems that clears NCA and SDAIA guidance, sits in a Saudi-region cloud, and integrates with the Tier-1 banking and ministry stack that most programmes already run on.
ChatGPT Enterprise is a great product, but it's OpenAI-hosted, one-size-fits-all, and doesn't integrate deeply with your internal data or systems. A custom build gives you deeper knowledge integration, model choice (including open-source), your cloud region, and role-based access tied to your identity provider. If you don't need those things, ChatGPT Enterprise is fine and we'll say so.
Four to eight weeks for a first working version. That covers document ingestion, the chat UI, SSO integration, basic role-based access, and an initial evaluation set drawn from your team's real questions. Longer builds add multi-tenancy, advanced governance, deeper system integrations, bilingual output formatting, and continuous retraining pipelines that keep the assistant fresh as your knowledge base changes.
It depends on data-residency and workload. If data can go to a vendor API, Claude and GPT-4-class models via Azure OpenAI or AWS Bedrock give the best quality-per-effort. When data must stay on your infra, we use open-source models (Llama, Mistral, Qwen) — often lightly fine-tuned on your content — and benchmark against the closed-model baseline.
The ingestion pipeline runs on a schedule and re-indexes new or updated documents automatically. For high-change sources (a wiki, a ticketing system, a document management system) we set up webhook-driven updates so changes appear in the assistant within minutes rather than the next nightly run.
Yes. Role-based access tied to your SSO provider means the assistant only retrieves documents the user is entitled to see. If HR docs are restricted to HR, the assistant honours that boundary. We test this explicitly in evals — one of the eval categories is 'user of role X asks about restricted document Y' — because access-control bugs in retrieval are the most damaging kind.
Ongoing cost depends on usage and model choice. For a mid-market rollout on hosted models, expect a per-user monthly cost in the same order of magnitude as ChatGPT Enterprise, plus the compute you already run. For open-source deployments the cost profile shifts to hardware and DevOps. We produce a cost model with each proposal so there are no surprises.
Yes. For Riyadh clients we default to Saudi-region cloud (AWS or GCP in KSA), work with local Saudi partners where Saudization requires it, and design for NCA and SDAIA guidance from the start of the engagement. The regulatory shape is treated as a delivery input, not something we discover at UAT.
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SM Stratagem builds custom chatgpt development in Manama, Bahrain. Private ChatGPT, your data. Deployed on your infra. Grounded and cited. Book a scoping call.
SM Stratagem builds custom chatgpt development in Muscat, Oman. Private ChatGPT, your data. Deployed on your infra. Grounded and cited. Book a scoping call.
We'll scope the first release, define the eval set, and give you a build plan you can hand to any engineering team — ours or yours.