For operators in Doha, we run ai agent development projects that leave you with production systems your team can maintain, not a vendor-only black box.
We build ai agent development for teams in Doha that need working software, not a slide deck for next quarter's steering committee. The buyers we work with in Doha tend to sit inside energy, finance, and sports infrastructure, and they want ROI they can point to at a board meeting. So our default is agents that take real actions inside your systems, with logs, permissions, and a rollback path, measured and iterated before anything touches production traffic. Every project ships with docs, evals, and a runbook the next engineer can pick up cold, without a knowledge-transfer week. We deliver across Qatar and the GCC in English and Arabic, with a project lead who owns delivery end-to-end rather than a chain of handoffs. The reason clients bring us back for the second and third ai agent development project is the handover: docs, evals, runbook, and a person who picks up the phone. If the project has already stalled once, the shape of the first release was usually wrong — that's fixable in a week, not a quarter.
Buyers in Doha 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.
Agents that draft the email, book the meeting, update the record, or open the ticket — with a clear audit log of what changed, when, and why.
Every tool call is scoped to what the agent is allowed to do, and destructive actions require confirmation until they've been shown to be safe. No blast radius.
When an agent misfires — and they will — you can see exactly what it did and undo it. That's a product requirement for us, not an afterthought.
Agents are evaluated on whether the task finished correctly, not on whether the tokens read nicely. We track completion rate as the headline number.
Research a prospect, draft a personalised outreach, log it in the CRM, book the meeting. The rep reviews and clicks send.
Triage inbound tickets, look up related history, take a first pass at a resolution or escalate, and update the record.
Agents that watch for schema drift, adjust downstream mappings, and open a PR for human review before anything ships.
For QatarEnergy contractors, QFC-registered firms, and ministries in Doha, we deliver AI agents inside existing vendor frameworks and procurement rules. Compliance is a delivery input, not a surprise at UAT.
Less than the sales pitch. We ship agents that operate inside a well-defined scope with permissions, logs, and human approval for anything reversible or expensive. Fully autonomous agents make sense for narrow, low-stakes workflows. For anything that touches customers, money, or production data, the agent is a copilot, not a replacement.
LangGraph and OpenAI's tool-calling APIs cover most of what we build. For long-running, multi-step workflows with retries and durable state we bring in Temporal. The framework isn't the interesting part — the interesting part is defining tools carefully, writing eval tasks that reflect real work, and instrumenting so you can see what the agent tried and why.
Least-privilege tool design, dry-run mode by default for destructive actions, mandatory approval for anything above a threshold, and a full audit log of every tool call. We also run agents against a red-team eval set that specifically tries to trick them, and any regression blocks the release.
A single-purpose agent (one workflow, one system to touch) is usually four to six weeks. Multi-tool agents that operate across several systems take eight to twelve. Most of the work isn't the model — it's defining tools cleanly, building eval tasks, and integrating with the source systems safely.
Yes, as long as the system has an API or a stable UI. We prefer APIs, obviously, but we can also drive UIs when that's the only path. For enterprise systems (Salesforce, Dynamics, SAP, ServiceNow, etc.) we've integrated most of the common ones and can move quickly.
Task-completion rate on a labelled eval set is the headline number. Alongside that we track cost per task, latency, human-intervention rate, and error class breakdown so you can see where the agent needs work. Everything lands in a dashboard your team owns after handover.
Yes. Public-sector and energy-adjacent work in Doha typically requires sitting inside an existing vendor framework and delivering under strict procurement rules. That's the shape we default to. We don't take POC-only work in Qatar — it wastes everyone's time — so we scope for production from the start.
SM Stratagem builds computer vision development in Doha, Qatar. Vision for real environments. Edge or cloud, your call. Handles lighting and drift.
SM Stratagem builds ai development in Doha, Qatar. Discovery to deployment. Measured on real usage. Handover-ready. Docs and evals included.
SM Stratagem builds rag development in Doha, Qatar. Retrieval that finds the right doc. Grounded, cited generation. Ingestion pipeline you own.
SM Stratagem builds ai agent development in Muscat, Oman. Agents that take real actions. Permissioned and logged. Rollback baked in. Book a scoping call.
SM Stratagem builds ai agent development in Dammam, Saudi Arabia. Agents that take real actions. Permissioned and logged. Rollback baked in.
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.