AI & AUTOMATION

AI system integration

Connect intelligent tools to the work they support.

BUILT AROUND YOUR BUSINESS

Connecting AI to a live system gives its output consequences. We agree data boundaries and tool permissions, then test the connection with clear rules for uncertain or failed actions.

0207 183 9270

Connect intelligent tools to the work they support.

Connecting AI to a live system gives its output consequences. We agree data boundaries and tool permissions, then test the connection with clear rules for uncertain or failed actions.

An automation is useful when it handles a clearly defined task reliably. We decide what it can access, where it should stop and who reviews important decisions before connecting it to live business tools.

Data pipeline engineer workstation.
AI system integration — planned around real work.

Make the important
work easier to do.

01

Interface review

For AI system integration, we start by reviewing interface review. We identify what already works and which decisions your team needs to make.

02

Data boundaries

We agree how data boundaries will fit the people and tools involved. Dependencies are reviewed before the implementation is scheduled.

03

Tool permissions

We check tool permissions in a realistic working journey. The result records any limitations and the person responsible for follow-up.

Clear deliverables. Shared expectations.

Interface review

Show the important journey before production and review what people see at each step. We include loading, empty and error states so the design explains how the experience behaves.

Data boundaries

Identify the records and documents that can be used, who owns them and how they are structured. We review quality and mapping before connecting the information to another system.

Tool permissions

Agree which records and actions each person can use. We check the boundaries across screens, searches and exports, rather than relying on a hidden button to protect information.

Integration tests

Use examples from real work, including incomplete and unexpected inputs. The checks give your team a visible way to decide whether the result is ready and which issues still need attention.

From a trigger to a useful outcome.

01

A form arrives

An agreed event starts the process with only the data it needs.

02

An agent checks the request

The assistant works from trusted sources and checks the task boundaries.

03

Rules route the next step

Business rules decide the route. Missing information goes to an exception queue.

04

A person approves the action

A person reviews important changes before anything is sent or committed.

Understand. Build.
Check. Hand over.

Discover

Discuss the real task, existing systems and constraints. Record what success looks like before choosing a solution.

Plan

Review the structure and agree the scope, responsibilities and acceptance examples. Set a realistic sequence for delivery.

Deliver

Build the agreed work in reviewable stages. Check the important details with your team and explain decisions as they are made.

Launch & support

Test the finished journeys, agree the launch and explain ownership. Discuss ongoing support separately from the initial build.

Build on what
already works.

An automation is useful when it handles a clearly defined task reliably. We decide what it can access, where it should stop and who reviews important decisions before connecting it to live business tools.

Platform choices follow the requirements. We review existing accounts, data formats and supplier agreements before proposing replacements or additional subscriptions.

Before anything connects

  • A real example of the repeated task
  • Tool owners and data boundaries
  • Approval rules and failure contacts

Access should match the task. Your business keeps ownership of its accounts and records.

Useful intelligence. Clear boundaries.

ILLUSTRATIVE ACCEPTANCE SCENARIO

Checking AI system integration in practice

Ask the assistant to retrieve approved data and attempt an action beyond its scope. Confirm the interface permissions, audit record and fallback before letting the agent interact with live business systems.

Your project uses examples agreed with your team. This scenario explains the checks to consider; it is not a completed client case study.

Controlled access

Agents receive only the tools and data needed for the agreed task. Sensitive actions require suitable approval.

Practical checks

Real examples are used to evaluate answers, tool use and fallback behaviour. Uncertain output should be reviewed.

People stay involved

There is a route to a person when the assistant cannot help. Owners can review errors and stop a workflow.

A proposal you
can understand.

Choose the level of work that fits your goal. We confirm the price after reviewing the requirements and list recurring and third-party costs separately.

One defined outcome

Focused project

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  • Interface review
  • Data boundaries
Discuss this scope
A wider working system

Connected delivery

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  • Interface review
  • Data boundaries
  • Tool permissions
  • Integration tests
Discuss this scope
Care and improvement

Ongoing partnership

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  • Regular review
  • Agreed support coverage
  • Planned improvements
  • Clear reporting
Discuss this scope

A little preparation.
A better starting point.

  • A real example of the repeated task
  • Tool owners and data boundaries
  • Approval rules and failure contacts

You do not need a finished specification. A real example, a clear goal and someone who knows the current process are enough to begin.

What a useful
partnership should feel like.

Sample perspectives for this service. Verified client testimonials will replace these with permission.

ILLUSTRATIVE · NOT A CLIENT REVIEW
“We wanted interface review explained clearly, so everyone knew what the project needed to achieve.”

Business owner · sample perspective

ILLUSTRATIVE · NOT A CLIENT REVIEW
“Having data boundaries agreed before delivery made it easier for our team to review the work and ask the right questions.”

Project lead · sample perspective

Clear answers.
Before you commit.

Where does AI system integration begin?

We start with interface review, then agree what data boundaries needs to cover. A real example from your business helps us define the work accurately.

What will we receive?

Your proposal sets out interface review, data boundaries, tool permissions, integration tests. The handover records the agreed setup, the checks completed and the responsibilities that remain with your team.

Can an agent take actions without approval?

Only within explicitly agreed permissions. Payments, sensitive changes and important customer communications should pass through a suitable human approval step.

How do you decide the price?

We quote for the agreed deliverables, complexity and support needs. Hosting, subscriptions, advertising spend and third-party charges are identified separately.

How will we check that the work is ready?

We use realistic examples to check tool permissions and integration tests. Your team reviews the important journeys before the work is signed off.

What happens after launch?

We explain the handover and maintenance needs. Ongoing support is a separate agreed scope with clear responsibilities and a review schedule.

Let’s talk about
AI system integration.

Tell us what you want to improve, what you use today and any deadline you need us to consider.