You will get an automated pipeline that pulls data from your documents automatically
Project details
Most businesses still copy data from documents into spreadsheets by hand. I build the pipeline that does it instead. Your file goes in, Claude API extracts and validates the data, and the result lands exactly where you need it, with no manual re-typing and no missed fields. Every pipeline is tested on your own sample documents before it goes live, and I build with direct API integrations to keep things stable and your ongoing costs low.
AI Algorithms
Linear Discriminant AnalysisAI Applications
Natural Language Understanding, Text RecognitionAI Development Language
PythonAI Models
GPT-4What's included
| Service Tiers |
Starter
$199
|
Standard
$499
|
Advanced
$899
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 10 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | - | - | |
Detailed Code Comments | - | - | - |
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | - | - | - |
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | |||
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | - | - | - |
Source Code | - | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$75 - $250
Additional Revision
+$50Frequently asked questions
About Tomas
Make & n8n Automation Expert | AI Document Processing
Usti nad Labem, Czech Republic - 5:27 am local time
I build the pipeline that does that instead.
WHAT I BUILD
Automated document processing pipelines on Make and n8n. Typical flow: incoming file (email, folder, form) → data extraction via Claude or OpenAI API → output to Sheets, Airtable, or any downstream system → notification or auto-reply.
RECENT PROJECT
Client: electrical inspection firm (200 reports/month)
Problem: technicians submitted reports with recurring formatting errors. Admin manually reviewed and corrected each one.
Solution: Make pipeline + Python that catches formatting issues and flags errors before the admin opens the file.
Result: 4 hours saved per complex inspection report.
PRODUCTION-TESTED PIPELINE
Gmail Invoice Processing:
- Gmail watches for emails with PDF attachments
- PDF passed to Claude API for structured data extraction: invoice number, vendor, amount, tax, due date, currency, confidence score
- Router: high-confidence invoices auto-logged to Sheets + Drive + vendor auto-reply / low-confidence invoices flagged in Slack for manual review
- Built via direct API integrations to maximize stability and minimize your credit costs
TOOLS
Make, n8n, Claude API, OpenAI API, Python, Supabase, Power Automate, Google Sheets, REST APIs
WHO I WORK WITH
Companies where someone is manually copying data from PDFs or emails into spreadsheets, processing the same file type repeatedly, or building reports by hand from data that already exists somewhere.
If you can describe the manual step you want to eliminate, I'll tell you in the first message whether it's buildable, how long it takes, and what it costs.
Steps for completing your project
After purchasing the project, send requirements so Tomas can start the project.
Delivery time starts when Tomas receives requirements from you.
Tomas works on your project following the steps below.
Revisions may occur after the delivery date.
Build the pipeline
Connect your document source and destination, then configure the Claude API extraction.
Test on your samples
Run your real sample documents through it and tune extraction accuracy until it's solid.