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Agentic AI

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Overview

Scope

Capabilities

Process

Use cases

FAQ

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AI systems that work toward a goal — not just answer a single prompt.

What this service is

Agentic AI refers to AI systems that pursue a goal: deciding on steps, using tools, and acting on information rather than producing one response to one question. LINIARITY helps businesses work out where that approach is useful and how to apply it with sensible limits.

Most people know AI as a chat window: ask a question, get an answer. Agentic AI goes a step further. An agent is given a goal and a set of tools, and works through the steps needed to reach it — gathering information, making decisions within set limits, and taking action.

For a business, the question is rarely "can AI do this?" but "should it, and with what oversight?" That's the practical work: choosing suitable tasks, defining what an agent may and may not do, and keeping people appropriately in the loop.

What it can cover

  • Identifying tasks suited to AI agents
  • Designing agent behaviour and boundaries
  • Connecting agents to business tools and data
  • AI agents
  • Task automation
  • Human oversight
  • Tool use

Areas of work

  1. Use-case discovery

    Finding the tasks in a business where an agent could genuinely help — and where it shouldn't be used.

  2. Agent design

    Defining the goal, the steps, and the decisions an agent is allowed to make.

  3. Tool and data connections

    Giving an agent access to the information and tools it needs, and nothing more.

  4. Guardrails and oversight

    Setting limits, approval points, and review so people stay in control.

  5. Evaluation and iteration

    Checking how an agent performs on real tasks and improving it over time.

How we approach it

  1. Identify

    Choose a task worth handing to an agent, and define what success looks like.

  2. Design

    Decide what the agent can do on its own, what needs a person, and what it must never do.

  3. Build and connect

    Assemble the agent and connect it to the tools and information it needs.

  4. Test and supervise

    Try it on real work with oversight in place, then adjust before relying on it.

Where it's useful

  1. Repetitive research or triage

    For example, gathering and sorting information so a person can decide what to do with it.

  2. Drafts for human review

    For example, preparing first versions of routine work that a person checks and approves.

  3. Coordinating several tools

    For example, carrying a task across systems that don't otherwise talk to each other.

Common questions

What is an AI agent?
An AI system given a goal and a set of tools, which works through the steps needed to reach that goal instead of only replying to a single prompt.
Will an agent act without any oversight?
That's a design choice. How much an agent may do on its own — and where a person must approve — is defined deliberately for each use case.
Which AI models or platforms are used?
Tooling is chosen to suit the task and the business. Specific platforms are discussed while scoping rather than assumed up front.

Curious where AI agents could fit?

Describe a task or process and we can talk through whether an agent is the right tool.

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