Process automation
Automation of repetitive tasks with human review where it matters: we classify requests, prepare drafts and move data between tools, with records and escalation on each case.
What we solve
We map the current workflow and its exceptions before automating anything. Only work with recognisable inputs and an output a person can validate gets automated.
Every automation leaves a trace: what it did, with which data and which cases were escalated to a person. Errors are recorded and reviewed, not hidden.
To choose a first process, compare a frequent task with a recognisable input, a checkable output and someone who can review it. If the steps, permission to use the data or responsibility for exceptions are still unclear, clarify them before automating.
Common problems
- Classifying emails, requests or documents takes hours each week
- Repetitive drafts (answers, reports, listings) are written by hand
- Information does not reach the right person in time
- Workload peaks force avoidable overtime
An illustrative example
Before: a small business receives requests by email and messaging. One person reads them all, sorts them into folders and writes a first answer for each one.
After: requests classify themselves by topic and urgency, and each arrives with a draft answer. The person reviews, corrects and sends; doubtful cases are flagged for priority review.
A proposed test case for this example: if a request omits a date the business needs, the draft must flag the missing date and go to review, without inventing it or sending a reply on its own.
An illustrative scenario explaining the service; not the outcome of a real customer nor a promise of results.
What the engagement includes
- A map of the current workflow with its exceptions
- An automation implemented and tested with real cases
- Human review and escalation rules
- An activity and error log
- A usage guide with the system's limits
What we need from you
- For the first enquiry, describe what starts the task, where the data lives and what result needs review
- One fictional or anonymised complete input and one incomplete input, with the expected output; do not send credentials or sensitive data
- The tools involved and the steps where information is copied or reviewed
- Authorisation to use the data and tools involved
- One person who validates tests and reviews uncertain cases during the first weeks
Scope and costs
Scope is agreed in writing: which process, which inputs and outputs, which human review and which observation periods. We start with one bounded process that allows learning.
Where the automation uses AI models or third-party services, their usage cost is estimated separately. No time estimate is a savings guarantee: our cost guide explains why.
Frequent questions
Can automation make mistakes?
Yes, which is why we design human review, limits and records from the start. Risky or doubtful cases always pass through a person.
Do I need to change tools?
Not necessarily. We work with your current tools where possible and integrate what is missing.
How do we know it works?
We define a simple baseline first: time, errors or response time. We also agree a complete input, an incomplete one and the expected result for each, including when a person must intervene. We compare the chosen measure after an agreed observation period; one successful test alone does not demonstrate savings.
What happens with unusual cases?
They are defined as exceptions from the design: they escalate to a person with all gathered context, instead of forcing an automatic answer.
Keep exploring
What process automation costs an SME
Compare tasks before choosing your first automation
Scope depends on the process, data and existing systems. We assess feasibility, risk and applicable obligations before proposing a solution.
What the project delivers
- Connected workflows
- Verifiable drafts
- Records and escalation
