Historical data
For Predictive workflows, we start by reviewing historical data. We identify what already works and which decisions your team needs to make.
Use forecasts with clear limits and oversight.
A forecast is an estimate, not a certainty. We agree the prediction target, review the source data and decide how uncertainty is shown before using the output in a business decision.
0207 183 9270A forecast is an estimate, not a certainty. We agree the prediction target, review the source data and decide how uncertainty is shown before using the output in a business decision.
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.

For Predictive workflows, we start by reviewing historical data. We identify what already works and which decisions your team needs to make.
We agree how prediction target will fit the people and tools involved. Dependencies are reviewed before the implementation is scheduled.
We check uncertainty checks in a realistic working journey. The result records any limitations and the person responsible for follow-up.
Review the current requirements with the person who knows the work. Agree the boundaries and useful examples before delivery.
Prepare the working detail for review, with time to ask questions and resolve assumptions.
Check the agreed implementation against realistic tasks and record the result.
Explain the handover and confirm who owns the next change or request.
An agreed event starts the process with only the data it needs.
The assistant works from trusted sources and checks the task boundaries.
Business rules decide the route. Missing information goes to an exception queue.
A person reviews important changes before anything is sent or committed.
Discuss the real task, existing systems and constraints. Record what success looks like before choosing a solution.
Review the structure and agree the scope, responsibilities and acceptance examples. Set a realistic sequence for delivery.
Build the agreed work in reviewable stages. Check the important details with your team and explain decisions as they are made.
Test the finished journeys, agree the launch and explain ownership. Discuss ongoing support separately from the initial build.
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.
Access should match the task. Your business keeps ownership of its accounts and records.
Define the prediction and the decision it supports, then test it on suitable historical data held out from development. Review uncertainty and unsuitable cases before allowing a prediction to influence a business action.
Your project uses examples agreed with your team. This scenario explains the checks to consider; it is not a completed client case study.
Agents receive only the tools and data needed for the agreed task. Sensitive actions require suitable approval.
Real examples are used to evaluate answers, tool use and fallback behaviour. Uncertain output should be reviewed.
There is a route to a person when the assistant cannot help. Owners can review errors and stop a workflow.
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.
You do not need a finished specification. A real example, a clear goal and someone who knows the current process are enough to begin.
Sample perspectives for this service. Verified client testimonials will replace these with permission.
“We wanted historical data explained clearly, so everyone knew what the project needed to achieve.”
Business owner · sample perspective
“Having prediction target agreed before delivery made it easier for our team to review the work and ask the right questions.”
Project lead · sample perspective
We start with historical data, then agree what prediction target needs to cover. A real example from your business helps us define the work accurately.
Your proposal sets out historical data, prediction target, uncertainty checks, decision review. The handover records the agreed setup, the checks completed and the responsibilities that remain with your team.
Only within explicitly agreed permissions. Payments, sensitive changes and important customer communications should pass through a suitable human approval step.
We quote for the agreed deliverables, complexity and support needs. Hosting, subscriptions, advertising spend and third-party charges are identified separately.
We use realistic examples to check uncertainty checks and decision review. Your team reviews the important journeys before the work is signed off.
We explain the handover and maintenance needs. Ongoing support is a separate agreed scope with clear responsibilities and a review schedule.
Tell us what you want to improve, what you use today and any deadline you need us to consider.