Automation & workflows
Your repetitive tasks handed to reliable workflows, with AI where judgment is needed, and alerts when something goes wrong.
Not everything needs an agent. A large share of back-office work is solved by a well-designed workflow: I connect your tools, automate the repetitive chains (sorting, data entry, follow-ups, reporting) and only add AI where it brings judgment. All of it supervised: a workflow that fails should alert you, not carry on silently.
Key facts
0
manual rekeying on automated processes
7 days
for a first useful workflow in production
100%
of failures visible: alerts, logs, statuses
What I build
Business process automation
Email triage and dispatch, data entry, follow-ups, reporting: repetitive chains executed by workflows plugged into your tools.
n8n · Workflows · Back-office
AI-augmented workflows
AI inserted at the right step of the workflow to classify, extract, summarize or draft. The rest stays deterministic, and therefore predictable.
LLM · Classification · Extraction
Custom integrations
CRM, ERP, email, spreadsheets, internal tools: I connect them through APIs and webhooks, including when no off-the-shelf connector exists.
API · Webhooks · CRM · ERP
The promise
Repetitive work runs on its own, under control.
Before / after
The same tasks rekeyed by hand every day
A workflow that sorts, processes and files on its own
An automated workflow that fails silently
Failures that are visible, alerted and retried
The stack
n8n
Make
Zapier
Python
TypeScript
API
Webhooks
Claude
Straight answers
Which processes should be automated first?
High-volume, low-judgment repetitive tasks: email triage, data entry, follow-ups, reporting, syncing between tools. A quick audit identifies the ones with the biggest payoff, often within days.
n8n, Make, Zapier or custom code?
n8n for most cases: self-hostable, versionable, extensible with code. Make and Zapier for simple, quick needs. Custom code when the logic outgrows what a visual tool can maintain cleanly. I choose based on your case, not my habits.
What happens when a workflow fails?
It tells you. Alerts, logs, a status for every run, the ability to retry: I design how it fails before I design how it works. A workflow that fails silently costs more than the manual task it replaced.
Do my automations need AI?
Not always. When the rule is clear, a deterministic workflow is enough and costs less. AI comes in where judgment is needed: classifying an ambiguous email, extracting data from a document, drafting a reply.
Contact
Ready to go from demo to production?
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