Turning AI into an operational capability
Artificial intelligence can go beyond generating answers or analysing information. Agents make it possible to build solutions that can take part in tasks and processes, consult different sources, interact with tools and carry out actions to achieve specific objectives.
At LurNova we design agents to operate in different contexts and perform specific functions, according to the needs of each project.
They can work individually or in coordination, specialise in specific functions, connect to systems and internal applications, and even draw on specific knowledge to do their work.
These capabilities allow them to work alongside people and take part in different stages of a process, from looking up information to carrying out actions.
What is an AI agent?
An AI agent is a system designed to pursue an objective and take the actions needed to achieve it within defined conditions.
Unlike an assistant that simply responds to a query, an agent can analyse information, decide which steps to take, use tools, query systems and carry out actions as a task unfolds.
For example, it can locate information across different sources, analyse documentation, access an application, complete an administrative step or prepare an output for a person to review.
In this way, an agent can chain different steps together to move towards an objective, combining the information it consults with the tools and actions needed to complete the task.
How we develop our AI agents
Each agent responds to a specific need. That is why we start from the work it must do to define the capabilities, information, tools and controls it needs to fulfil its role.
We understand what the agent needs to do.
We analyse the process, the people involved, the information required and the actions to be carried out in order to clearly establish the agent's objective and the limits within which it must operate.
We define which tasks AI can carry out and which require a person's intervention or validation.
We define what it needs to do its work.
We determine what information it must consult, which tools it needs to use, which systems it must interact with and which model or combination of models best suits each function.
Depending on the complexity of the case, we design a specialised agent or an architecture in which several agents collaborate and share out the tasks.
We connect the agent to the environment in which it must operate.
We develop the agent and connect it to the information sources, applications, APIs and corporate systems it needs to work.
We set permissions, rules and control mechanisms that determine which information it can use and which actions it is authorised to take.
We test how it performs and improve its capabilities.
We test the agent in real situations, assess the quality of its results and analyse how it responds to different scenarios.
Based on its use, we can adjust its behaviour, add new tools and gradually expand the tasks it can perform.
One agent or a team of agents
Not every process requires the same solution. When the task is well defined, a single specialised agent can handle it. If it requires combining different functions, several agents can collaborate to achieve the same objective.
In these cases, an orchestrator agent can coordinate the work of the specialised agents, distribute tasks and use their results to decide how the process should continue. For example, one agent can gather information, another analyse it and a third act on the result.
Autonomy with oversight and control
An agent's ability to act autonomously must match the nature of the task and the impact of its results. That is why we define what it can do, which information it can access and at which points a person must step in.
These criteria make it possible to distinguish tasks that can proceed autonomously from actions that require review or approval. An agent can, for example, prepare a proposal and leave its validation to a person before continuing.
Frequently asked questions
What is the difference between an AI agent and an assistant?+
An assistant usually focuses on answering questions or helping a person during an interaction. An agent can have a broader objective and take different steps to achieve it, including using tools or carrying out actions.
What tasks can an AI agent perform?+
It depends on the use case. It can search for and analyse information, work with documentation, query systems, prepare content, handle administrative steps, use applications or coordinate different tasks within a process.
Can it connect to the organisation's systems?+
Yes. Agents can connect to applications, databases, APIs, document repositories and other tools when the project requires it and the necessary access mechanisms are in place.
Can an AI agent work with the organisation's internal knowledge?+
Yes. We can develop agents that use documentation and other authorised knowledge sources to contextualise their responses and carry out their tasks.
Can an agent carry out actions autonomously?+
Yes, when the use case allows it. The level of autonomy is defined according to the task and the controls required. Certain actions can be executed automatically, while others may require validation by a person.
What is a multi-agent system?+
It is a solution in which several specialised agents collaborate to achieve an objective. Each agent can take care of a different part of the work and share information or results with the others.
Do agents replace people?+
That is not the approach we take when designing these solutions. We aim to determine which tasks AI can take on and where a person's experience, judgement or validation is needed. The split depends on each process and its requirements.
Which AI models do the agents use?+
It depends on the needs of the project. We can work with different models and select the most suitable ones according to the task, the information involved and the security, performance and operational requirements.
How is what an agent can do controlled?+
We define permissions, access, available tools, operating rules and oversight points. In addition, when the project requires it, we can add mechanisms to log and monitor its activity.
Can we start by automating just part of a process?+
Yes. In many cases it makes sense to start with a specific task, validate how it works and gradually expand the agent's capabilities as results come in and new needs arise.
Other services
AI strategy and consultancy
We define where AI can add the most value and how to put it into practice.
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AI applied to knowledge
We turn knowledge into a capability made accessible through AI.
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Intelligent automation
We apply AI to automate processes that until now required manual intervention.
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AI training and adoption
We prepare teams to bring AI into the way they work.
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From specific tasks to new ways of working
Agents take artificial intelligence beyond simple queries and integrate it into work processes. At LurNova we design solutions that work alongside people, connect information with action and open up new possibilities for organising and carrying out work.