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Services · AI Workflow Automation & Integration

Connect your systems and automate the work that slows you down

We connect your applications, data and APIs, and automate specific workflows. We use AI agents where reading and understanding text helps. Where fixed rules do the job, we use ordinary automation, because it is simpler, cheaper and more reliable.

The problem

Disconnected tools and manual work limit growth

People copy data between systems, requests sit in inboxes, exceptions are handled from memory, and nobody can see the whole process.

Adding AI to a messy process rarely helps. What helps is connecting the right systems, defining the workflow clearly, and deciding what can run on its own, what needs a person's approval and what happens when something goes wrong.

Who this is for

  • Operations and technology leaders with repetitive work that spans several systems
  • Companies that need their applications, devices and data to work together
  • Teams exploring AI agents who want to use them safely in real processes

Common use cases

  • Connecting applications, databases and partner or device APIs
  • Document and data processing
  • Sorting, routing and tracking requests
  • Internal assistants that can only see the company data you allow
  • Alerts, escalations and approval steps for people
  • Workflows built on field and device data

Scope

What you can expect

01

A review of the process and systems, with a clear scope for automation

02

The integrations and workflows, built

03

Clear permissions, data access and approval points

04

Handling for exceptions, plus logging and monitoring

05

Tests, including checks on the steps that use AI

06

Documentation and a guide for running it day to day

Our approach

We use AI to work faster. People are responsible for the result.

  1. 01

    Map the workflow

    Write down how the work happens today, so you have a baseline to measure against.

  2. 02

    Pick the right kind of automation

    Use AI agents for steps that need interpretation, and ordinary automation for steps that follow fixed rules.

  3. 03

    Add controls from the start

    Permissions, approvals by people, audit trails and monitoring.

  4. 04

    Measure and improve

    Compare with the baseline and tune the workflow once it is live.

Engagement models

Start small, then grow with confidence

We do not force every project into the same package. Scope and commercial terms are agreed with you after we understand the problem.

Fixed-scope discovery

A short, paid piece of work to clarify the problem, review your current system, and agree the scope, risks and plan before you commit to a bigger build.

Paid pilot

A small project with a fixed end date that tests the approach on one real workflow or module, with clear criteria for success.

Milestone-based delivery

Set deliverables with agreed acceptance criteria, for work that can be scoped with confidence.

Monthly engineering

A dedicated team working in your process on an ongoing roadmap, with a shared backlog, regular reports and clear responsibilities.

FAQ

Common questions

When should we use an AI agent, and when not?

Use agents for steps that need interpretation, such as unstructured documents or free-text requests. Use conventional automation for fixed rules. Many good solutions combine both.

How do you keep AI automation safe?

We limit what each part can see and do, add a person's approval where mistakes would matter, log every action, and watch how it behaves once it is live.

Can you integrate with our existing systems?

Yes, that is a big part of our work. We look at your systems and APIs first, so we can tell you what is realistic.

Which workflow would you like to fix first?

Tell us what you are trying to achieve. We will give you an honest view of the right way forward.