AI agent development

Build an agent around a real business responsibility

An effective AI agent needs a clear job: understand an incoming request, find relevant knowledge, prepare a useful result and take only the actions it is allowed to take. Open for AI works with organisations to define and develop that system around their own processes, information and users.

We start with the work you want to improve. A service team might need help assembling an answer from approved documents. An operations team might need to coordinate the next steps in a case. A commercial team might need a repeatable way to prepare relevant material from product and buyer knowledge. The development brief identifies the task, its boundaries and the point at which a person should decide.

What we can develop together

• Knowledge agents: retrieve relevant information from approved sources and show the evidence behind an answer.
• Workflow agents: prepare, route and track work across the systems and teams involved in a process.
• Research and preparation agents: organise supplied information into drafts, comparisons and decision support.
• Business assistants: help a defined group of users complete a particular task within their permissions.

These are engagement directions, not a fixed catalogue of identical implementations. The appropriate design depends on your source systems, the information available and the consequences of an incorrect action.

Define the boundary before connecting the tools

During scoping, we map which sources the agent can read, which operations it can request and which decisions require approval. Read-only assistance and actions that change a business record have different requirements. The system should make those differences visible to the people using and operating it.

For each integration, we establish the identity used, the permissions granted, the expected response and the recovery path if the dependency fails. Sensitive actions need explicit checks. Repeated requests need protection against duplicate effects. Uncertain inputs need an escalation route rather than an invented answer.

Evaluate the work, including the exceptions

A demonstration is an early learning step. Before a broader release, a useful evaluation set includes normal cases, incomplete information, conflicting documents, inaccessible sources and requests beyond the agent's authority. Acceptance criteria should describe observable behaviour, including when the correct response is to ask for help.

Question	Evidence to examine
Does it complete the intended task?	Representative cases reviewed by the people responsible for the work.
Does it use the right information?	Source selection, access restrictions and traceable supporting material.
Does it stay within its authority?	Approval steps, rejected operations and exception handling.
Can the team operate it?	Monitoring, ownership, incident handling and an agreed change process.

Plan implementation around your organisation

For organisations in Saudi Arabia, discovery should capture Arabic and English requirements, the actual working environment, data-handling expectations and the teams responsible for reviewing the implementation. These requirements belong in the project scope from the beginning. A regional address alone does not establish a system's deployment location or compliance position.

If you are still choosing a starting point, explore our agentic AI consulting. If your priority is connecting an agent to existing applications, see AI solutions and integration.

Bring one workflow to the first conversation

Tell us what starts the process, who owns it, what information is used, what a good outcome looks like and where work currently slows down. Examples with confidential details removed are enough for an initial discussion. We can use that context to identify the discovery work, development scope and next decision.

Discuss an AI agent development project.

What to expect from an AI agent development company

Your developer should be able to explain the intended job, its limits and how it will be tested before proposing an elaborate multi-agent system. A production plan needs more than an attractive chat interface: it needs accountable business ownership, access to the right information and a way to stop or escalate a task that cannot be completed safely.

For a Saudi business, a useful discovery brief identifies Arabic and English users, source document languages, operating hours, approval responsibilities and any constraints your organisation places on its information. We work from those requirements rather than assuming that every organisation needs the same architecture.

Single agent, multiple agents or ordinary automation?

A predictable sequence may be better served by deterministic software. An agent becomes more useful when interpreting requests, selecting relevant knowledge or choosing among permitted next steps matters. Multiple agents can separate responsibilities, but each additional handoff needs its own clear inputs, outputs and failure handling. The design should earn that complexity.

Agree what the development handover includes

A scoped project can include an evaluated agent workflow, integration interfaces, source configuration, an operational runbook and an acceptance record. We agree the particular deliverables, deployment environment, ownership arrangements and support responsibilities before delivery. Source access and ongoing model or infrastructure costs should be explicit in the engagement.

A practical first development brief

Bring a redacted example of an incoming request, the approved information needed to resolve it and the output you expect. Name one acceptable exception and one action the agent must never perform without permission. These examples make the initial conversation about behaviour and business value rather than a list of model names.

You can also explore our own Forge marketing and branding platform, Post email campaign platform and Echo consultation follow-up product. They address specific workflows; a custom development engagement is a separate route for requirements those products do not cover.