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AI Agents & Automation

Agents that do the work, with humans in charge

AI agents work best on well-defined workflows with clear escalation to people. We find those workflows, redesign them, and build agents that run inside your systems and your cloud.

Most agent projects aim too wide

40%+

of agentic AI projects are forecast to be cancelled by the end of 2027 because of rising costs, unclear value or weak risk controls.

Source: Gartner, June 2025

What goes wrong

  • Agents given open-ended jobs they cannot reliably finish
  • Automating a broken process instead of fixing it
  • No audit trail or human checkpoint
  • Savings assumed, never measured

What we do instead

  • Target well-defined, high-volume workflows with clear rules
  • Redesign the workflow before automating it
  • Build in human review, escalation and logging
  • Measure time, error rate and cost against a baseline

Who it's for

SME leaders

Your team spends hours on repetitive admin, and you need help without hiring a data team.

Enterprise teams

You need agents with the documentation to go through security, risk and works council review.

Product managers

You want AI agents inside your product that behave predictably for customers.

How it works

Typical timeframe: 4‑10 weeks per workflow. Every engagement is scoped to your situation after the discovery call.

Week 1

Pick and map the workflow

We choose one workflow with clear inputs, rules and volume, map every step and exception, and measure today’s time and error rate.

Deliverables
  • Workflow and exception map
  • Baseline metrics
  • Automation design with human checkpoints
Weeks 2‑5

Build and shadow

We build the agent inside your tools, then run it in shadow mode alongside your team so you can compare its output before it acts on its own.

Deliverables
  • Working agent in your environment
  • Shadow-mode comparison
  • Escalation and logging setup
Weeks 6‑10

Go live and measure

We roll out in stages, track savings and errors against the baseline, and train the people who now supervise the agent.

Deliverables
  • Staged production rollout
  • Savings and quality report
  • Runbook and team training

You leave with

  • An agent running a real workflow in production
  • Measured savings against your own baseline
  • Clear human checkpoints and a full audit trail
  • A team trained to supervise and improve it

Workflows that suit agents

  • Invoice, order and document processing
  • Support triage and draft replies
  • Lead research and CRM updates
  • Compliance checks and report preparation
  • Internal IT and HR request handling
  • Data entry across systems without APIs
Why well-defined workflows

In independent tests, leading agents completed about 30% of open-ended office tasks (TheAgentCompany, Carnegie Mellon, 2025), yet scored above 83% on structured workflow execution (CRMArena-Pro, Salesforce AI Research, 2025). We build for the second kind.

Common questions

Do we need an agent or just automation?

Often just automation. If the steps are fixed, a rules-based workflow is cheaper and more reliable. We use agents where judgement on messy inputs is needed, and tell you which is which.

Where does the agent run, and who sees our data?

In your cloud or tenant wherever possible, with EU data residency options. We document every data flow for your data protection officer.

What happens when the agent gets it wrong?

It is designed for that. Low-confidence cases go to a person, every action is logged, and actions above a set risk level always need human approval.

Will this replace our staff?

In our experience it moves people from repetitive steps to review, exceptions and customer work. We design the rollout with your team, not around them. If you have a works council, we involve it early and provide the documentation it needs.

Start with one workflow

Book a 30-minute call and tell us where your team loses the most time. We will tell you whether an agent, simple automation, or neither is the right fit.