Find the right starting point.
Review the process, identify avoidable manual work, and leave with a practical automation plan.
Less busywork.More forward motion.More progress.
Automation consulting that connects your tools and takes repetitive work off your hands.
Sample data demo
See the work move.
From scattered data to a ready-to-read report.
- 1
Collect
Pull data from your sources.
- 2
Validate
Check, clean, and standardize.
- 3
Report
Compile and deliver the report.
Illustrative final report
Live sample
From scattered data to a ready-to-read report.
Demo projects on synthetic data. Client credentials never appear in public demos or repositories.
Live sample · n8n · PostgreSQL
Run the real sample
The action below calls the demo endpoint once. The returned records, counts, and anomaly are rendered as the report you see.
This demo runs against a small synthetic dataset. No alert is actually sent to anyone.
Built around your bottleneck.
Start with the outcome and the stubborn manual step. The tooling follows from the process.
Automate a recurring workflow.
Connect your existing tools and handle a defined process, with testing, error handling, and handover documentation.
Connect the difficult parts.
Add custom Python and API processing when your tools need more than standard integrations.
Three more ways the pieces connect.
These optional demos use synthetic inputs and remain separate from the illustrative workflow above.
n8n · API · HubSpot
Lead Capture and Enrichment
Enter a work email and watch a real n8n workflow derive the company from the domain and write a tagged contact into HubSpot, the same pattern used for real client lead intake.
This demo writes a tagged, non-production contact to a live CRM. It is automatically removed within 24 hours.
Python · PostgreSQL · n8n
Custom Data Processing with Python
Submit a few deliberately messy records and watch a real n8n workflow call a Python API that normalizes them, matches them against a reference list, scores each match, and records every row it had to reject.
This demo uses synthetic data. Nothing you submit is stored or logged.
Python · OpenAI vision · n8n
Invoice & receipt extraction
Pick a sample invoice and a vision model pulls the vendor, dates, and line items into a strict schema. Plain Python then re-adds the totals and flags any document whose numbers do not reconcile.
This demo uses synthetic invoices. Nothing you submit is stored or logged.
A clear path from first look to handover.
Four practical stages, with scope, support, and acceptance criteria made explicit.
- 01
Assess
Understand the current process, desired result, systems, constraints, and failure risks.
- 02
Design
Map the workflow, responsibilities, data movement, error behavior, and acceptance criteria.
- 03
Build and test
Implement with synthetic or approved test data, exercise success and failure paths, and document configuration requirements.
- 04
Handover
Deliver workflow exports, setup instructions, tests, documentation, and a short walkthrough. Warranty and ongoing support are defined separately.
Experience that starts with the process.
I’m Alvin, an automation consultant based in the Philippines. I bring more than 20 years in reporting and BI to practical workflows built with n8n, Python, and APIs.
More about me and my workTell me what keeps repeating.
Tell me what repeats, where it gets stuck, and what you would like to happen instead. I’ll review your request and reply within two business days.
We’ll clarify the workflow and whether an automation project is a good fit. Scope, pricing, and delivery are agreed separately.
Before you send it
What types of processes can be automated?
Suitable examples include lead handling, notifications, recurring reporting, data movement, validation, follow-up, and API-based processing. An assessment determines whether automation is appropriate.
Can you work with our existing tools?
I first review the tools, available APIs, account permissions, data requirements, and operational constraints. Compatibility is confirmed before scope is agreed.
Who owns the completed automation?
The intended delivery model uses client-owned accounts and production infrastructure. Exact ownership and licensing terms are documented in the project agreement.
How are credentials and business data handled?
Public demos use synthetic data. Client credentials are not placed in public demos or repositories. Production access, retention, and security responsibilities are agreed before work starts.
What happens after delivery?
Every delivery includes agreed documentation, testing, and handover. Warranty, monitoring, maintenance, and future changes are scoped separately.