Grange IT Group
Implementation

AI agents and agentic workflows

Some work isn't a single fixed step. It runs across a few decisions in sequence: read the enquiry, look something up, draft a reply, send it to the right person. An agent can carry out that kind of multi-step task, choosing what to do next within limits you set, rather than following a rigid script. We build agents on tools you can keep, with human oversight and guardrails as part of the design.

  • Built on tools you can keep
  • Human oversight by design
  • Start with a single workflow
The result

What an agent changes

The routine middle of a job gets handled on its own, so your team's time goes to the cases that genuinely need a person.

  • Multi-step work handled with a degree of judgement
  • Staff freed from chasing and coordinating between systems
  • A workflow that adapts within limits you control
What we build

What goes into an agent that works

The interesting part isn't the model. It's the limits, the connections and the oversight around it.

Workflow agents

An agent that handles a task across several steps, such as triaging an enquiry then drafting and routing a response, grounded in your own systems and content.

Tool use and integration

Agents work by using your tools: looking things up, updating records, sending messages. We connect them to the systems your team already runs.

Guardrails and oversight

Clear limits on what an agent can do, with a person signing off the steps that matter, so it stays useful without acting beyond what you've agreed.

Start small and measure

We prove one workflow end to end before extending it, so you can see it working and weigh the saving before committing further.

A worked example

An agent handling an enquiry

Take a shared inbox where every message needs reading, looking up and routing. An agent can carry the routine cases from start to finish.

  1. 1

    It reads the enquiry

    The agent takes a new message and works out what it's about: a quote request, a support question, or something that needs a person straight away.

  2. 2

    It gathers what it needs

    It looks the customer up in your systems, checks their account or order, and pulls together the details a reply would need.

  3. 3

    It drafts and routes

    For a routine request it drafts a reply grounded in your own information, then sends it on for someone to approve, or handles it directly where you've allowed that.

  4. 4

    A person stays in the loop

    Anything unusual, sensitive or high-value is flagged for a person, with a clear record of what the agent did and why.

Automation or an agent

Where an agent fits, and where it doesn't

For predictable work, plain automation is simpler, cheaper and more reliable, and we'll tell you when that's the answer. An agent earns its place only when a task needs judgement across several steps.

Plain automation

Fixed, predictable steps

  • Best when the rule is always the same
  • When this happens, do exactly that
  • Cheap, fast and easy to reason about
  • No judgement involved, and that's the point

An AI agent

Judgement across several steps

  • Best when the next step depends on what it finds
  • Reads, decides and acts within limits you set
  • Handles the messy cases a fixed rule can't
  • Kept in check with guardrails and human sign-off
How it works

From one workflow to a working agent

We prove a single workflow end to end before extending it, so you see it working before you commit.

  1. Define

    We pick one multi-step task, agree what good looks like, and decide where a person stays in the loop.

  2. Prototype

    A working agent on a narrow slice, so you can try it against real cases early.

  3. Build

    We develop the full workflow with its guardrails, connected to your systems and permissions.

  4. Launch and oversee

    Roll it out, set up monitoring and sign-off, and agree how it's supported as it runs.

FAQs

Common questions

A few of the things organisations tend to ask before getting started.

Automation follows fixed rules: when this happens, do exactly that. An agent handles work that needs a little judgement across several steps, deciding what to do next within the limits you set. For simple, predictable tasks, plain automation is usually the better and cheaper answer, and we'll tell you when that's the case.

Start with a conversation

Book a free, no-obligation call. We'll discuss your business, where AI might help and where it might not, and the most sensible first step.

Book a free consultation