Artificial Intelligence · AI Agents
AI agents for enterprises in Saudi Arabia: assistants that take action, with approval and audit
GoAgile designs, builds and runs AI agents that read requests, use your ERP, email and service systems, and complete the work, inside the permissions, approval steps and audit rules you set. We have deployed agents for enterprises, in the cloud and on premises.
- Agents that act in your ERP, finance and service systems
- A person approves anything that matters
- Cloud, private cloud or fully on-premises
- Not just answer
- ActNot just answer
- Human in the loop
- ApproveHuman in the loop
- Private deployment
- On-premPrivate deployment
- Languages
- AR + ENLanguages
What it is
What are AI agents?
An AI agent is software that uses a large language model to understand a goal, decide the steps, use tools such as your ERP, email and databases, and complete the task within rules you set. Unlike a chatbot that only answers questions, an agent acts, and asks a person to approve the steps that carry risk.
Agents work best on repeatable, rule-bound work that spans several systems: raising purchase requests, chasing invoices, handling IT and HR requests, checking documents against policy and preparing reports. Each agent gets its own identity, its own limited permissions and a record of everything it does.
We build agents on three foundations: knowledge (RAG over your documents), tools (secure connections to your systems, including the Model Context Protocol where it fits) and controls (guardrails, approval gates, evaluation and audit). The model can be a cloud service or an open model running on your own servers.
Key facts
- Does
- Plans, uses tools and completes tasks
- Connects to
- ERP, CRM, email, ticketing, databases and documents
- Controls
- Least-privilege access, approvals and an audit log
- Knowledge
- RAG over your policies and records
- Hosting
- Cloud, private cloud or on-premises
What we build
From a single agent to a governed agent platform
Six workstreams. Start with one agent and one process, then reuse the platform for the next.
Agents designed around a real process
We pick a process worth automating, map the steps and decisions, and decide what the agent does alone, what it proposes and what a person approves. Single agents and multi-agent workflows are both options, and we prefer the simplest design that works.
- Process mapping and agent scope
- Single agents and multi-agent workflows
- Decision rules and escalation paths
- Memory and context handling
- Instructions and replies in Arabic and English
- A written list of what the agent may not do
What you get
An agent with a defined job, a defined boundary and a person accountable for it.
Secure access to the systems where work happens
Agents are only useful when they can act. We connect them to your ERP, CRM, finance, email and ticketing systems through APIs or the Model Context Protocol, with every action limited to what the agent is allowed to do.
- ERP actions in Dynamics 365, SAP, Odoo, Oracle, Zoho and TallyPrime
- Email, calendar and document systems
- Ticketing and service desk tools
- Model Context Protocol servers for approved tools
- Read-only first, write access once proven
- Safe retries that never double-post
What you get
Agents that complete tasks inside your systems, not beside them.
Agents that know your policies and records
Retrieval-augmented generation gives the agent your documents, policies and data as its source of truth, with answers cited and access checked for each user.
- Document ingestion, chunking and embeddings
- Hybrid search and re-ranking
- Permission-aware retrieval
- Citations on every answer
- Re-indexing when documents change
- Retrieval quality measured on your questions
What you get
Answers and actions based on your facts, with sources a reviewer can open.
Controls that keep an agent inside its lane
Guardrails run outside the model, so a clever prompt cannot talk an agent out of its limits. High-risk actions wait for a person.
- Least-privilege permissions for each agent
- Approval gates by risk and amount
- Prompt-injection and data-leak defences
- Personal data masking and content filters
- Spending, rate and scope limits
- Kill switch and rollback
What you get
Agents your risk, security and audit teams can sign off.
Tested before go-live, watched after
We build test sets from your real cases, measure accuracy and failure modes before launch, and monitor every run afterwards.
- Test sets drawn from real requests
- Pass or fail checks on tool use and answers
- Red-team tests for misuse and injection
- Run traces and cost tracking
- Quality and drift dashboards
- Regression tests on every change
What you get
Evidence that the agent works, and early warning when it stops.
Cloud or on-premises, run like any critical system
Agents run in the environment your data rules require. We deploy, monitor and support them with the same discipline as any production system.
- Cloud, private cloud or on-premises
- Open models on your own GPUs when data must stay in-house
- Secrets, identity and network controls
- Backups, versioning and rollback
- Support and improvement cycles
- Hand-over and training for your team
What you get
An agent in production with an owner, a runbook and a support path.
How we work
From one process to a working agent
Most first agents reach production in weeks, not quarters, because we start narrow.
- 1
Choose
We pick one process with clear rules, real volume and a measurable result.
- 2
Design
Agent scope, tools, approvals and guardrails, agreed on paper with the process owner and security.
- 3
Build
The agent, its knowledge and its integrations, built in a test environment with sample data.
- 4
Test
Real cases, red-team tests and sign-off by the process owner, security and risk.
- 5
Launch
A limited rollout with approvals switched on and every run monitored.
- 6
Improve
We review traces and cost, then widen the agent's scope step by step.
Reference
Where agents pay off, and which type of AI to use
Two tables we use in the first workshop.
Agents we commonly build
| Agent | What it does | Systems | Human approval |
|---|---|---|---|
| Procurement agent | Checks requests against policy and budget and drafts purchase orders | ERP, policy library | Orders above a set limit |
| Finance operations agent | Chases invoices, matches payments and drafts reconciliation notes | ERP, bank statements, email | Postings and write-offs |
| IT service desk agent | Resolves common requests, resets access and escalates incidents | Ticketing, directory | Access to sensitive systems |
| HR assistant agent | Answers policy questions and starts onboarding and leave workflows | HR system, policy library | Contract and pay changes |
| Compliance agent | Checks documents and records against rules and logs exceptions | Document store, ERP | Final sign-off |
| Customer service agent | Resolves cases, updates orders and hands over with context | CRM, ERP, WhatsApp | Refunds and exceptions |
Chatbot, RAG assistant or AI agent?
| Type | What it does | Best for | Risk |
|---|---|---|---|
| Rule-based chatbot | Follows scripted flows | Simple, fixed FAQs | Low |
| RAG assistant | Answers from your documents, with citations | Knowledge questions | Low to medium |
| AI agent | Plans and acts through tools, with approvals | Multi-step work across systems | Controlled by permissions and approvals |
Most projects combine them: a RAG assistant for knowledge and an agent for action.
Technology
Vendor-neutral models, tools and hosting
We choose the model and platform that fit your data rules and budget, including open models on your own servers.
Models
Build and orchestrate
Private serving
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Built for Saudi enterprises
Agents that respect your data, your rules and your regulators
Local data, governance, security and language are designed in from the first workshop.
Your data stays where you decide
Data residency is a design choice, made first. Agents and models can run on your servers or in a Saudi-hosted environment, so personal and sensitive data stay under your control. We map what each agent touches against the PDPL and your data classification before we build.
- A data map for every agent
- On-premises or in-Kingdom hosting
- No training on your data by default
- Retention and deletion rules
- Masking before any external call
- Regular access reviews
What you get
A clear answer when an auditor asks where the data went.
Accountable by design
Every agent has an owner, a risk rating and a record. We align the approach with SDAIA's AI Ethics Principles and your own policies, so you can explain what an agent does and who answers for it.
- An agent register with owners and risk ratings
- A change and approval process
- Explainable results with linked sources
- An incident procedure
- A review cadence
- Alignment with SDAIA principles, the PDPL, and sector rules such as NCA and SAMA
What you get
AI you can explain to a regulator or a board.
Security treated as part of the design
Agents widen the attack surface, so we apply the controls you already trust: identity, least privilege, logging and testing, and we test specifically for prompt injection.
- Separate identity for each agent
- Least-privilege tool access
- Untrusted text kept apart from instructions
- Full logging of actions
- Penetration and red-team testing
- Secrets kept out of prompts
What you get
An agent that is hard to abuse and easy to audit.
Arabic and English from day one
Instructions, answers and documents in Arabic and English, with Arabic-capable models chosen and tested on your own content.
- Arabic and English evaluation sets
- Dialect handling where needed
- Right-to-left output
- Hijri and Gregorian dates
- Arabic document ingestion
- Choice of Arabic-capable models, including open models
What you get
Agents your Arabic and English speakers both trust.
Why GoAgile
Why enterprises build agents with GoAgile
Demos are easy. These are the things that matter after the demo.
Agents in production
We have deployed AI agents for enterprises, so we design for what appears after the demo: permissions, approvals, cost and support.
Controls first
Guardrails, approvals and audit are designed before the first tool is connected.
RAG and data engineering
Retrieval, integrations and data quality are built by the same team as the agent.
On-premises when it matters
Open models on your own servers when data must stay in the Kingdom.
Your systems, not a new silo
Agents work inside Dynamics 365, SAP, Odoo, Oracle, Zoho and your own software.
Local and accountable
A Riyadh team working in Arabic and English, with ISO 27001 certified practices.
More from AI
Explore our other AI services
Each one stands alone and works better with the others: knowledge, agents, automation and the governance around them.
- AI Consulting & StrategyFind where AI pays off, set the guardrails and build a roadmap you can fund.View service
- Machine Learning & Data ScienceForecasting, anomaly detection and language models, trained and run where your data lives.View service
- Generative AI SolutionsRAG assistants, copilots and private LLMs grounded in your documents and systems.View service
- Intelligent Process AutomationDocuments, approvals and back-office work automated with RPA, AI and human review.View service
- AI Chatbots & Virtual AssistantsArabic and English assistants on web, WhatsApp and voice, handing off to people.View service
Which process would you hand to an agent first?
Tell us the process, the systems it touches and the approvals it needs. We will propose an agent, the controls and a pilot plan.
Plan an AI agent →Questions answered
AI Agents FAQs
What are AI agents?
What is the difference between an AI chatbot and an AI agent?
Are AI agents safe for enterprise use?
Can AI agents run on-premises?
Which processes suit AI agents?
How long does it take to build an AI agent?
How do you stop an agent from making things up?
What is the Model Context Protocol (MCP)?
Do your agents work in Arabic?
How do you measure whether an agent is working?
Talk to an AI agent specialist
Tell us the process you want to automate and the systems it touches. We will respond with an approach and a pilot plan.
Why GoAgile for AI agents?
Agents designed with controls first, deployed for enterprises, in the cloud or on your own servers.
- Agents that act, with approvals and audit
- RAG, tools and guardrails built together
- On-premises deployment when data must stay
- ISO 27001 information security practices