Agents that get work done.
Rsquare builds autonomous AI agents that plan multi-step tasks, call your APIs and tools, and complete real business workflows for banks, government, and enterprise across the GCC, with human approval at the moments that matter.
Beyond chatbots. Agents that act.
A chatbot answers a question. An agent finishes the job. Rsquare designs agentic systems that break down a goal, plan the steps, call the right tools and APIs, and carry a task through to completion, inside your existing systems, not a demo sandbox.
A complete agentic capability map.
From single-task automation to coordinated multi-agent systems.
Task Planning & Orchestration
Agents that decompose a goal into ordered steps, decide what to do next based on results so far, and adapt the plan when conditions change.
Tool Use & API Integration
Agents that call your internal APIs, databases, and third-party services directly, so work actually gets done in your systems, not just described.
Multi-Agent Systems
Specialist agents that collaborate on complex work: one agent researches, another drafts, another verifies, coordinated end to end.
Human-in-the-Loop Approval
Every consequential action pauses for sign-off from an authorized person before it executes, with a full record of what was proposed and who approved it.
Memory & Context Management
Agents that retain relevant context across a task and across sessions, without losing track of what has already been done or decided.
Monitoring & Observability
Every agent run is logged, traceable, and reviewable, so you can see exactly what an agent did and why, at any point in its execution.
Autonomy your auditors can approve.
Agentic AI does not mean unsupervised AI. Every agent we build proposes; an authorized person approves the actions that matter. Every step is logged. This is why the Central Bank of Bahrain named Rsquare winner of its Reg-Tech Innovation Challenge, and why our AI runs inside regulated institutions today.
- Human approval workflows
- Full execution audit trails
- Bounded, reviewable agent actions
Cloud, hybrid, or fully private agents.
Agentic systems architected around your data sovereignty, compliance, and cost requirements.
Cloud Agents
Frontier-model agents with no infrastructure to manage. Sensitive data is masked before any call leaves your network.
Hybrid Agents
Planning and reasoning in the cloud; execution and sensitive data handling stay inside your network, with selective routing.
On-Premise Agents
Open-weight models running on your own hardware, orchestrating agents entirely within your infrastructure. Air-gapped capable.
We build agents in three stages.
Map the Workflow
We identify the multi-step tasks worth automating and the tools and APIs an agent will need to complete them.
Build & Harden
Our engineers build, test, and stress the agent against real edge cases and failure modes before it touches production data.
Operate & Improve
Ongoing monitoring, guardrail tuning, and continuous improvement as the agent handles more of the workflow.
Part of a wider AI practice.
This is one of four specialist capabilities inside our AI practice. Explore the others, or see how they come together.
What we build with.
Which workflow eats the most staff time?
That's the one worth handing to an agent. Book a 30-minute assessment.
Schedule a Free Consultation