Service 02 / Workflow automation

Build one workflow that removes the repetitive step.

One end-to-end automation with AI at the decision point, connected to your existing tools, with a human approval step where the risk is real.

2 to 4 weeks€3,000 to €6,000Operations, support and finance teams with a repetitive process

The short answer

I build one workflow end to end: trigger, data collection, AI decision or extraction, the action in your existing tool, and the exception path. The scope is fixed, the integration is documented, and the automation is measured against the baseline from the audit.

The problem

People copy data between a form, a spreadsheet, an inbox and a CRM. The work is not hard, but it consumes hours and introduces typos.

Approvals sit in someone’s inbox. The process is waiting, not working, and nobody can see where it is stuck.

An automation exists in a no-code tool, but it fails silently when a field changes or an API returns an error.

The team has no audit trail for what the automation decided, so exceptions are handled by asking the person who built it.

What you get

Outcomes

  • Hours removed from a measured workflow, not a generic productivity claim.
  • Fewer manual keying errors because validation happens before the write-back.
  • A visible exception queue instead of silent failures.
  • A documented integration and a runbook your team can own.
  • A before/after report with the baseline, the new cycle time and the remaining manual work.

Deliverables

  • A workflow design with trigger, steps, systems and owners.
  • The AI step: classification, extraction or a structured decision with a defined output schema.
  • Integration to the tools you already use, through an API, webhook or file exchange.
  • Validation rules and confidence thresholds.
  • A human approval or review step for the cases that need one.
  • Error handling, retries and a dead-letter path for failed items.
  • Structured logs so every automated action can be traced.
  • A runbook and a handover session with the team that operates it.
  • A before/after measurement on the same samples used for the baseline.

Evidence

Fit and boundaries

This is a good fit when

  • One workflow with at least five hours a week of repetitive work.
  • A process owner who can approve the rules and the exceptions.
  • At least one system with an API, export or structured file.
  • A team that wants to keep its existing tools.

This is not a fit when

  • No process owner, or a process that changes every week.
  • A decision that requires a regulated professional judgement with no human review.
  • No access to the systems involved. A screenshot is not an integration.
  • An attempt to replace a whole team with an agent. This is one workflow, not a reorganisation.

How it works

  1. 01

    Baseline the current workflow

    We agree the samples, the time measurement and the definition of a successful outcome. The baseline is frozen before the build starts.

  2. 02

    Build the happy path

    Trigger, AI step, validation and write-back. The common case is automated end to end before the exceptions are added.

  3. 03

    Design the failure path

    What happens when the model is unsure, the API is down or the data is invalid? Every workflow needs a visible place for the item to land.

  4. 04

    Measure and hand over

    The same samples are run through the new workflow. You get the before/after numbers, the runbook and a session with the people who own it.

Pricing and timing

Questions

Do we have to replace our current tools?

No. The workflow is built around the tools you already use. If a tool has an API, a webhook or a reliable export, it can usually be part of the automation.

Where does the human stay in the loop?

Wherever the cost of a wrong action is high, or the model is not confident. The approval step is designed into the workflow, not added after an incident.

What happens when the automation fails?

Every item has a visible failure path: a review queue, a retry, or an alert. Silent failure is the thing that turns an automation into a liability.

How is the time saving measured?

On the same samples used for the baseline: time per item, manual touches, cycle time and exception rate. The report shows the range, not a single best case.

Can you maintain it afterwards?

Yes, through the monthly automation retainer. It covers monitoring, exception review and a small improvement block. It is optional; the handover is designed so your team can own the workflow.

Written by

Marius Boroica is an independent AI automation engineer in Cluj-Napoca, Romania. He designs AI workflows, document pipelines and internal assistants, and connects them to the tools a team already uses. NVIDIA Certified Professional: Gen AI LLMs.

Page last updated: October 2026

Next step

Tell me what is breaking.

A 30-minute call is enough to decide whether this service is the right one. If it is not, I will name the smaller engagement that is.

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