Evaluation set
For AI performance optimisation, we start by reviewing evaluation set. We identify what already works and which decisions your team needs to make.
01A useful starting point
Improve the assistant using evidence from real work.
A change to a prompt or source can improve one answer and break another. We use an evaluation set and error records to make changes that can be checked consistently.
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.
02The everyday problem
Make the important
work easier to do.
Error review
We agree how error review will fit the people and tools involved. Dependencies are reviewed before the implementation is scheduled.
Prompt changes
We check prompt changes in a realistic working journey. The result records any limitations and the person responsible for follow-up.
03Your agreed scope
Clear deliverables. Shared expectations.
Evaluation set
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.
Error review
Make the state of the work visible and give important failures an owner. We agree which events need attention, how they are reported and what information the responder should receive.
Prompt changes
Check the agreed implementation against realistic tasks and record the result.
Regression checks
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.
04A connected working system
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.
05Our delivery process
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.
06Your existing tools
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.
07Quality and safeguards
Useful intelligence. Clear boundaries.
Checking AI performance optimisation in practice
Evaluate an existing version against a fixed set of representative examples before changing prompts or retrieval settings. Repeat the same checks afterward and review regressions as well as improvements.
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.
08Scope and investment
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.
Focused project
Request a quote- Evaluation set
- Error review
Connected delivery
Request a quote- Evaluation set
- Error review
- Prompt changes
- Regression checks
Ongoing partnership
Request a quote- Regular review
- Agreed support coverage
- Planned improvements
- Clear reporting
09Ready for the first conversation
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.
10Client perspectives
What a useful
partnership should feel like.
Sample perspectives for this service. Verified client testimonials will replace these with permission.
“We wanted evaluation set explained clearly, so everyone knew what the project needed to achieve.”
Business owner · sample perspective
“Having error review agreed before delivery made it easier for our team to review the work and ask the right questions.”
Project lead · sample perspective
11Your questions, answered
Clear answers.
Before you commit.
Where does AI performance optimisation begin?
We start with evaluation set, then agree what error review needs to cover. A real example from your business helps us define the work accurately.
What will we receive?
Your proposal sets out evaluation set, error review, prompt changes, regression checks. 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 prompt changes and regression checks. 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.
12Start a conversation
Let’s talk about
AI performance optimisation.
Tell us what you want to improve, what you use today and any deadline you need us to consider.