AI Agent Development

AI agents that move from answers to action, under your control.

From Tunis, Uteek builds AI agents that understand a goal, query your systems and carry out a sequence of actions: finding information, updating a record, drafting a document or triggering a workflow. Each agent works within clear boundaries, with human approval at sensitive steps.

Schéma d’un agent IA enchaînant des actions entre CRM, ERP et messagerie, conçu par UteekUteek · Tunis
Artificial Intelligence

What is an AI agent?

An AI agent is a system that takes a goal, plans the steps needed to reach it and carries them out using tools such as APIs, databases, CRM, ERP, email or a web browser. Where a chatbot answers a question, an agent takes action. It might check stock levels, create an order, follow up with a customer and log the outcome, adjusting its path based on what it finds at each step.

At Uteek, we design AI agents for specific, repetitive tasks that involve several systems. We decide with you which tools the agent can use, which actions it may take on its own and which require human approval. Every decision is logged so it can be traced. This approach lets you automate complex processes while keeping full visibility over what happens inside your systems.

What we build with AI agents

Agents connected to your tools

Agents that read from and write to your CRM, ERP, spreadsheets or email through secure API connectors, using only the permissions they actually need.

Multi-step orchestration

Logic that breaks a goal into tasks, picks the right tool for each step and adapts what happens next based on the results it gets along the way.

Built-in human approval

Checkpoints where the agent submits its proposal to a team member before any sensitive action, such as external emails, payments, deletions or major changes.

Multi-agent systems

Several specialised agents working together, for example one for research, one for drafting and one for review, coordinated by an orchestrator agent.

Logging and traceability

A detailed record of reasoning, tool calls and outcomes, so you can understand every decision the agent makes and support internal audits with confidence.

Conversational and voice agents

Agents available through chat, email or voice that can handle a request from start to finish instead of simply replying to it.

Hand your repetitive tasks to an AI agent

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Why choose Uteek to build your AI agents?

An AI agent is only useful if it fits cleanly into your systems and stays under control, and that is exactly where we help.

Strong integration background

For over ten years, our developers have connected websites, mobile apps and business systems. That hands-on experience with APIs and data is what makes an AI agent reliable in a real environment.

Security by design

Minimal permissions, test environments, human approvals and activity logs: we agree with you on what the agent can do alone, what it must get approved and what it is never allowed to do.

Open choice of models

We work with APIs from the leading model providers as well as self-hosted open-source models, choosing the right option for your cost, performance and data confidentiality requirements.

A step-by-step approach

We start with a narrow use case, measure the results and then expand the agent’s autonomy gradually, in line with the trust your teams build in it over time.

Uteek in figures

+20Dedicated experts

+650Projects delivered

+120Clients served

+7Countries served

Frequently asked questions: AI Agent Development

What is the difference between an AI agent and a chatbot?

A chatbot holds a conversation and answers questions. An AI agent pursues a goal: it plans steps, calls tools such as a CRM, ERP or email system and carries out concrete actions. An agent may have a chat interface, but its value comes from what it does inside your systems, not just from what it says.

What tasks can an AI agent handle?

An AI agent can process an incoming request end to end: read an email, find the customer record, check availability, draft a reply or quote and update the CRM. It suits repetitive tasks that involve several tools and follow a recognisable logic, even when individual cases vary from one request to the next.

How do you keep control over an autonomous AI agent?

We limit the agent to the tools and data it needs, with precise permissions. Sensitive actions such as external emails, payments or deletions require human approval. Every step is logged, and stop rules halt the agent if something looks wrong. Its autonomy is then widened gradually, based on the results observed in practice.

Which AI models do you use for your agents?

We use APIs from the leading language model providers when reasoning quality and tool use are the priority. When confidentiality or cost requires it, we deploy open-source models hosted on your servers or in a cloud of your choice. The architecture stays modular, so the model can be swapped without rebuilding everything.

Can an AI agent connect to our ERP or CRM?

Yes, as long as these tools offer an API, an accessible database or usable exports. We build dedicated connectors with limited rights and, where needed, an intermediate layer that controls which operations are allowed. For older software, we assess the safest integration approach case by case.

How do we get started with an AI agent project?

We recommend starting with a proof of concept on a single process, built within a few weeks in a test environment. It lets you check how reliable the agent is on your real data, identify edge cases and make an informed decision about a wider rollout.

How do you measure the return on investment of an AI agent?

We define the indicators before development starts: handling time per request, volume processed without intervention, approval rate of the agent’s proposals, customer response time and error rate. These are compared with the starting point, which makes the gains measurable and helps prioritise the next improvements.

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