Look at the trigger, inputs, decisions, handovers and exceptions. Remove unnecessary steps before reproducing them in software.
Compare configuration, APIs, workflow tools, RPA and AI-assisted steps against the requirement. AI should have a defined role rather than being added to every task.
Agree validation, retries, alerts and a place for exceptions to be reviewed. Keep consequential actions behind the approvals the process requires.
We agree a bounded process, baseline measures and acceptance criteria. Delivery covers the connections and operating arrangements as well as the automated steps.
Assess APIs and supported integration routes first. Where screen-based automation is necessary, account for interface changes and the support it will need.
Compare handling time, rework, waiting and exception rates with the starting point. Include operating costs and maintenance when deciding whether to expand.
Some steps are predictable; others need context or authority. Define the boundary and approval points before allowing a system to change records or send communications.
Test missing data, duplicate events, unavailable systems and repeat runs. Agree who can update the process when suppliers, policies or working practices change.
These examples are starting points for discovery. Access, data quality and exception handling determine which parts are suitable to automate.
Move enquiries into the right queue, create tasks and track agreed follow-up, with clear rules for missing details and overdue work.
Extract or organise suitable information, validate required fields and send uncertain results for review before they reach another system.
Coordinate forms, checks and tasks across teams. Keep authorisation with the accountable person and record progress and exceptions.
Bring data together and flag differences for investigation. Agree source ownership, matching rules and review before relying on the result.
How delivery works
Define the problem, audience, dependencies and what a useful result would look like.
Map information, system connections, permissions, handovers and exceptions.
Review a bounded implementation against representative cases and agreed acceptance criteria.
Agree ownership, support, monitoring and how changes will be evaluated after launch.
Before we start
Start with a repeated task that takes time, creates rework or holds up a service. We help assess the opportunity and choose a focused first workflow with a clear way to measure the improvement.
We look for practical ways to connect your existing platforms, using their features and APIs where possible. Where another approach such as RPA is useful, we explain how it would work and how to keep it supported.
We build validation, clear progress tracking and recovery into the design. Your team can see work that needs attention and has an agreed way to resolve it, making the automation easier to operate day to day.
We agree useful measures at the start, such as handling time, rework, waiting or capacity. A focused rollout gives you evidence to compare with the starting point and helps you decide where further automation is worthwhile.
Tell us what starts the work, which systems are involved and where time is lost. We will help assess a manageable first scope and how to measure it.
