Connected nodes representing an automated workflow

AI & Automation

AI agents that finish the work, with people in control.

We build AI agents and automated workflows that read requests, look up data, take actions in your systems and ask for approval when a decision needs a human.

Typical first targets: Invoice, order, service-request and onboarding workflows

Overview

Automation that handles the messy middle.

Traditional automation breaks when inputs vary. AI agents can read an email, understand an attachment, check SAP, decide the next step from your rules, and either complete the task or prepare it for approval.

We design agents with clear boundaries: which tools they may use, which actions need sign-off, and how every step is logged. That keeps automation safe, explainable and easy to audit.

Agents connected to SAP, email, documents and APIs
Human-in-the-loop approval for sensitive actions
Full audit trail of every decision and action
Measured against cycle time, accuracy and cost per case

Business outcomes

What you can expect

Shorter cycle times

Requests are handled in minutes instead of waiting in queues.

Lower cost per transaction

People handle exceptions rather than every case.

Fewer errors

Validation against master data catches mistakes before they post.

Happier teams

Staff move from repetitive work to judgement and service.

Quality

Testing and data conversion on the critical path.

We invest more effort than most firms in testing and data conversion, because that is where projects succeed or fail.

What we deliver

Agent and automation services

We start with one high-volume process and expand once value is proven.

Process discovery

Identify the processes where agents remove the most manual effort, ranked by value and risk.

Finance and procurement agents

Invoice matching, vendor queries, purchase-request triage and collections follow-up.

Order and service agents

Order intake from email and PDFs, status queries and case routing.

HR and IT service agents

Onboarding tasks, policy questions and service-desk triage.

RPA modernisation

Make brittle bot scripts resilient by adding AI understanding of documents and exceptions.

Agent operations

Monitoring, exception queues, cost tracking and continuous improvement.

Approach

How the engagement runs

A structured method with clear milestones, so risk is visible early and decisions are made with facts.

Frame
Agree the business problem, the users, the data involved and the measure of success.
Prove
Build a working slice on your real data and test it with the people who will use it.
Harden
Add security, evaluation, monitoring and integration so it is safe to run in production.
Scale
Roll out, train users, track value and hand over a solution your team can own.

FAQ

Frequently asked questions

What is the difference between an AI agent and RPA?

RPA follows fixed screen steps. An AI agent understands unstructured inputs, decides the next step within rules you set, and uses systems through APIs. We often combine both.

Can agents change data in SAP?

Yes, through approved APIs and with permissions you control. Sensitive actions such as postings or payments can require a human approval step.

How do we keep agents safe?

Each agent gets a limited set of tools, spending and action limits, approval rules, and complete logging. We test edge cases before go-live.

Where should we start?

Start where volume is high, rules are clear and errors are recoverable, such as invoice processing or service-request triage.

Keep exploring

Related services and insights

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Learn more

AI Readiness Assessment

Two weeks, fixed scope: ranked use cases, data and risk check, and a pilot plan.