Ghaim builds secure AI agents that can reason over company knowledge, use approved tools and APIs, and execute multi-step workflows across enterprise systems—with AWS infrastructure, identity and observability underneath.
We keep the work tied to business outcomes: security, availability, delivery speed, cost control and a platform that can keep evolving after launch.
Employees can search, summarize and reason over approved company knowledge across documents, policies, product data and operational systems.
The agent experience is designed around real employee workflows rather than a generic chat window.
Agents can call APIs and approved tools to create tickets, update systems, retrieve account information, prepare reports or trigger workflow steps.
Permissions, human approval points and auditability are critical when an AI system can act rather than only answer.
Amazon Bedrock AgentCore provides building blocks for running, securing and observing agentic applications. We design the runtime, identity, memory, gateway and observability patterns around each use case.
This helps move agent projects from prototypes into controlled production environments.
Agents are only useful when they can retrieve the right business context. We build retrieval and data access layers with clear boundaries between users, departments and systems.
The architecture should prevent broad data access from becoming the default.
We define success around completion rate, accuracy, time saved, escalation rate and business outcomes.
A production agent needs evaluation, feedback loops and workflow ownership—not just a good demo.
Ghaim is an Advanced AWS Partner with AWS DevOps, Resilience Services and Cloud Operations Services Competencies, plus local presence through Riyadh and Dubai offices.
Validated capabilities across automation, CI/CD, Infrastructure as Code and cloud delivery practices.
Validated experience designing and improving reliable, recoverable AWS workloads.
Validated CloudOps capabilities spanning governance, operations, observability, auditing and cloud financial management.
An enterprise AI agent combines model reasoning with company data and approved tools so it can complete multi-step tasks, not only generate text.
Yes, provided the systems expose suitable interfaces and the security model defines what the agent is allowed to access or change.
AgentCore is an AWS platform for building and operating AI agents with capabilities such as runtime, identity, memory, gateways and observability.
We apply least-privilege identity, scoped tool access, logging, approval points, input/output controls and data-access boundaries appropriate to the workflow.
Yes. Model selection, retrieval data and evaluation should be tested against the specific Arabic use case, terminology and business process.
We will route the conversation to the right AWS or AI specialist and define the fastest useful next step.