Data re-entry, manual checks, recurring reports: time-consuming tasks cost your teams hours every week. Here is how to identify them, prioritise them, then hand them to AI agents, without writing a single line of code.
30%
of working time can be reallocated to higher-value work, according to McKinsey
5 steps
from raw data to finished deliverable, in a metered pipeline
0 code
required from business teams: you drop the files, ERHA processes them
A time-consuming task is a recurring task that eats time out of proportion to the value it produces: re-typing data from one tool into another, pulling figures out of a PDF, checking a document line by line, compiling the same report every week. Taken alone, each looks harmless; added up, they absorb a measurable share of working time, and of payroll.
These tasks share three traits: they repeat, they follow known rules, and they require no complex judgement. That is exactly what makes them automatable by an AI pipeline: humans keep the decisions, the machine does the processing.
Copying the same information from a file, an email or one tool into another.
Pulling figures, dates or references out of unstructured documents.
Checking a document line by line for consistency or compliance.
Compiling the same tables and summaries every week or month.
Routing requests, filing documents, preparing case files.
Comparing values against specifications and raising the alerts.
Every automation follows the same metered, traceable pipeline, from raw data to a ready-to-use deliverable.
List the team's recurring tasks and the time they actually consume.
Cross frequency, duration and rule simplicity: the best candidates stand out on their own.
Our team assembles the AI pipeline on your real data, inside your dedicated space.
The pipeline flags doubtful cases and re-processes them before returning the result.
You receive a ready-to-use deliverable, with the exact cost of every run.
Those that meet three criteria: high frequency, documented rules, no complex judgement. Data re-entry and document control are almost always the best starting points.
Studies converge around 30% of working time being reallocatable (McKinsey). At task level, a deliverable that took hours of manual processing is returned in minutes by the pipeline.
No. You drop your files into your dedicated space; ERHA builds and operates the pipeline. Your team keeps final validation of the deliverable.
We'll show you ERHA on your own use case, in 20 minutes.