Looking for N8N Automation Freelancer/Agency – Vertical Pricing Intelligence Platform

Jobs
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n8n Automation Freelancer/Agency– Vertical Pricing Intelligence Platform

We are building a data intelligence platform focused on structured pricing insights in the automotive services domain.

We’re looking for an experienced n8n freelancer or boutique automation agency to design and implement robust scraping and validation workflows.

Scope of Work

  • Automate data extraction from ~40–60 online sources

  • Handle structured and semi-structured formats including:

    • HTML web pages

    • Excel files

    • PDF documents

    • Images (OCR-based extraction where required)

  • Normalize extracted data into clean, structured fields

  • Store validated output in Excel (Nextcloud environment)

  • Implement:

    • Duplicate detection logic

    • Basic validation rules

    • Error handling & retry workflows

    • Alerting (Email / Slack)

    • Logging and monitoring

Ideal Profile

  • 2+ years hands-on experience with n8n (Cloud or self-hosted)

  • Strong background in web scraping and Excel/PDF parsing

  • Experience integrating OCR pipelines (image-to-text workflows preferred)

  • Experience building production-grade automation systems

  • Comfortable documenting architecture and conducting a short knowledge transfer session

Engagement Details

  • Remote

  • Target start: 01 Mar 2026

  • Fixed-price proposal preferred

  • Strong English communication required

We are looking for someone who can think in systems and design scalable, fault-tolerant automation workflows — not just basic scraping scripts.

7 Likes
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If you need i am available here:

I am one of top 50 verified template creators:

I am also capable of building custom community n8n node too:

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Check my recent gen ai projects… I built a native Android automation agent too. It’s worth a look:

I can build complex AI automations directly in code, not just inside n8n

I recently started posting my n8n work on YouTube with explanations:
https://youtube.com/@blankarray

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Fun fact… I even made an n8n workflow to find a few n8n project leads for myself so I truly believe in what I do…

9bSkKu
9bSkKu1220×1470 122 KB

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3

@n8ndev_bluru Hi — this is exactly the kind of infrastructure-level automation project I specialize in.

I’m Muhammad Bin Zohaib, Certified n8n Developer (Level 1 & 2), focused on building production-grade automation systems — not just scraping scripts.

I’ve built systems involving:

• Multi-source scraping (HTML, Excel, PDFs, OCR-based extraction)
• Structured normalization into enforced schemas
• Deduplication + validation logic
• Retry workflows + failure queues
• Logging, monitoring, Slack/email alerts
• API integrations and scalable modular n8n architecture

Relevant work includes:
– Dental booking system integrations with real-time APIs
– OCR-powered automation pipelines
– AI validation platforms
– Large-scale data extraction + enrichment systems
– Voice AI systems connected to backend scheduling

For your pricing intelligence platform, I would architect this as:

  1. Parallelized ingestion layer (rate-limited + monitored)

  2. Format-specific parsing modules (HTML/XLSX/PDF/OCR handlers)

  3. Normalization & schema enforcement layer

  4. Validation + duplicate detection engine

  5. Structured storage in Nextcloud Excel environment

  6. Monitoring, logging, and alert workflows

With 40–60 sources, stability and observability will matter more than speed of initial build.

Before finalizing a fixed-price proposal, I’d like clarity on:

• Update frequency per source
• Expected daily data volume
• Anti-bot or login-protected sources
• Hosting setup (n8n Cloud or self-hosted)
• SLA expectations

You can review my work here:
:brain: Project demos (videos + breakdowns): https://muhammad-ai-automations.notion.site/Muhammad-Bin-Zohaib-AI-Automation-Projects-29da292a241380f889c2e337a134c010
:open_mailbox_with_raised_flag: Email: [email protected]
:telephone_receiver: WhatsApp: +92 3360327970
:briefcase: LinkedIn: https://www.linkedin.com/in/mbz1415/

If this aligns, I’d be happy to schedule a short technical call and then submit a structured milestone-based proposal.

Looking forward to discussing.

4

To build a truly scalable Pricing Intelligence Platform, you need more than just data extraction; you need a resilient data pipeline. I will design and implement a production-grade n8n architecture that transforms fragmented automotive service data (Web, Excel, PDF, and Images) into a clean, actionable database within your Nextcloud environment.

​The Strategy: “System-First” Automation

​Instead of building 60 individual scripts that are hard to maintain, I will implement a Modular Architecture:

  • ​Multimodal Extraction Layer: * Web & Files: Automated parsing of HTML and Excel.

    • ​Vision AI (OCR): Integration of high-accuracy OCR pipelines to extract pricing data from images and complex PDF layouts.

  • ​The Normalization Engine: * A centralized logic block that maps various source formats into your specific “Automotive Service” data schema.

    • ​Validation: Automatic checks for data types, currency consistency, and missing fields.

  • ​Data Integrity & Deduplication: * Intelligence logic to ensure that if a source is scraped twice, or if multiple sources report the same data, your Nextcloud Excel sheet remains a “Single Source of Truth” without duplicates.

  • ​Fault-Tolerant Operations: * Error Handling: Automatic retries for temporary site timeouts.

    • ​Alerting: Real-time Slack or Email notifications only when a workflow requires human intervention (e.g., a source site changes its layout).

​Project Roadmap & Deliverables

  1. ​Architecture Design: Mapping the flow from 40–60 sources into the centralized Nextcloud storage.

  2. ​Development & OCR Integration: Building the n8n workflows with a focus on high-uptime and clean data output.

  3. ​Validation & Logging: Implementing the “Safety Net” (Error handling and monitoring logs).

  4. ​Knowledge Transfer: A recorded walkthrough and documentation of the system architecture so your team understands exactly how to manage and scale it.

​Why This Approach?

​By using n8n, we maintain a low-code flexibility that allows for rapid adjustments as your data sources evolve. My focus is on building a self-healing system—one that logs its own performance and alerts you proactively, ensuring your pricing insights are always accurate and up-to-date.

​Would you like me to create a quick technical breakdown of how we will handle the OCR-to-Excel portion of this workflow specifically?

5

This fits my work well. I design production-grade n8n pipelines for large-scale scraping and data normalization HTML, Excel, PDFs, and OCR from images with proper retries, logging, and alerting. I’ve built systems that handle deduplication, validation rules, and fault-tolerant ingestion into structured stores (including Excel/DB backends).

I focus on system design, not just scraping scripts: batching, monitoring, and failure isolation so workflows run reliably at scale. Happy to share a screenshot/video of a complex n8n workflow I’ve shipped and discuss your architecture.

6

Hi!

I’ve DM’ed you with all the relevant details.

Looking forward for your response.

Rohan

7

Hey @n8ndev_bluru

I’ve been doing data scraping for enterprise client using n8n for the past 3 years now. From simple ones to really complicated ones. I believe I can help you with it.

I’d love to scope the project out with you on a call together if you’re open to it.

Here’s my calendar link → https://cal.com/meet-ziya/30min?overlay=&overlayCalendar=true&duration=30

Best,
Ziya

8

Great scope — this is exactly the kind of infrastructure challenge where n8n’s modular design shines over custom scripts.

A few thoughts on the architecture before you commit:

Source heterogeneity is your biggest cost driver. 40–60 sources with HTML, Excel, PDF, and OCR means you can’t use one universal adapter. I’d structure this as: (1) a source registry workflow that stores each source’s extraction config, (2) a dispatcher that routes each source to the correct extractor sub-workflow, and (3) a shared normalization layer downstream. This way adding a new source is updating a config record, not rewriting code.

On the OCR layer specifically: For automotive pricing images (price lists, window stickers), a Vision AI node (GPT-4o or Claude) will outperform Tesseract significantly — especially with non-standard fonts and watermarks. Worth factoring into the architecture decision early.

Nextcloud + deduplication: If you’re storing to Excel on Nextcloud, deduplication gets tricky at scale. A lightweight SQLite or Supabase layer as an intermediate store handles dedup logic cleanly, then writes final validated data to Excel. This avoids the file-locking issues you’ll hit with concurrent write workflows.

I’ve built multi-source extraction pipelines with similar requirements (structured normalization, retry queues, validation rules, alerting). Happy to scope this out in more detail — what’s the expected run frequency and volume per source?

9

Hey Profile - n8ndev_bluru - n8n Community

I got you, I have been building all forms of automations for the past 2 years and have built 100s of flows for my clients. Have worked with all sorts of companies and gotten them 10s of thousands in revenue or savings by strategic flows. When you decide to work with me, not only will I build this flow out, but also give you a free consultation like I have for all my clients that led to these revenue jumps.

I have built a similar workflow like this for one of my clients. I can not only share that but also how you can streamline processes in your company for faster operations. All this with no strings attached on our first call.

Here, have a look at my website and you can book a call with me there!

Talk soon!

10

Hi n8ndev_bluru,

I specialize in building production-grade n8n automation systems exactly like what you’re describing – multi-source data extraction, normalization pipelines, and fault-tolerant workflows.

Why I’m the right fit:

:white_check_mark: 3+ years n8n experience (self-hosted + Cloud) building enterprise automation

:white_check_mark: Multi-format extraction expertise: HTML scraping (Playwright/Puppeteer), Excel parsing, PDF extraction, OCR integration (Tesseract/Google Vision)

:white_check_mark: Built similar pricing intelligence systems for B2B clients - 100+ sources, 10K+ records/day

:white_check_mark: Production-grade architecture: Error handling, retry logic, duplicate detection, Slack/Email alerting, comprehensive logging

My Approach for Your Project:

Phase 1: Architecture & Source Analysis

  • Map all 40-60 sources by format and structure

  • Design modular n8n workflows (separate flows per source type)

  • Define normalization schema and validation rules

  • Set up Nextcloud Excel storage with versioning

Phase 2: Core Workflows

  • HTML scraping with anti-detection (rotating proxies, user agents)

  • Excel/CSV parsing with error recovery

  • PDF extraction (tabular + unstructured)

  • OCR pipeline for image-based pricing data

  • Central normalization workflow (all sources → single schema)

Phase 3: Quality & Reliability

  • Duplicate detection (fuzzy matching for near-duplicates)

  • Multi-level validation (format, range, business logic)

  • Retry workflows with exponential backoff

  • Monitoring dashboard (success rate, error tracking)

  • Email/Slack alerts for failures

Phase 4: Documentation & Transfer

  • Architecture documentation

  • Workflow diagrams

  • Troubleshooting guide

  • 2-hour knowledge transfer session

  • 2 weeks post-launch support

Tech Stack I’ll Use:

  • n8n (self-hosted for better control)

  • Playwright/Puppeteer (dynamic HTML scraping)

  • Tabula/Camelot (PDF table extraction)

  • Google Vision API / Tesseract (OCR)

  • PostgreSQL (for deduplication tracking)

  • Nextcloud API (Excel storage)

  • Slack/Email (alerting)

What Makes This Production-Grade:

  • Fault tolerance: Each source runs independently - one failure doesn’t crash the system

  • Scalability: Parallel processing for 40-60 sources

  • Monitoring: Real-time alerts + weekly performance reports

  • Maintainability: Modular design - easy to add new sources later

Deliverables:

  1. Fully functional n8n workflows (documented, tested)

  2. Architecture documentation + workflow diagrams

  3. Knowledge transfer session (recorded)

  4. 2 weeks post-launch support

Sample Work: I’ve attached a sample of my n8n work – a similar multi-source data extraction system I built for a B2B client. Shows my approach to error handling, normalization, and monitoring.

[https://drive.google.com/file/d/1c5HhLgcvb_x2g3mQEAMD3pCa9IeEUIDV/view?usp=sharing]

Available for immediate start. Strong English communication (as you can see from this proposal). Based in Pakistan (PKT timezone), flexible hours.

Next Step: I’d love to jump on a 15-minute call to understand your exact source list and validation requirements. When works for you?

Best regards,

Hamza

[email protected]

11

I’m interested on the job as i have worked on something related

12

Hey :waving_hand:,

I’m Milan, with 8 years of experience in Business Automation and AI. Including 2 years at Apify working on enterprise-level browser automation.

Currently specializing in n8n, but also proficient in Python & Javascript.

Find out more about my work here:

If you think I might be a match, please:

Book a call here with me

Or reach out at [email protected]

Looking forward to hearing from you!

13

Hi @n8ndev_bluru,

This is right up my alley — I’ve built multi-source data extraction pipelines that handle exactly this kind of heterogeneous source complexity (HTML scraping, PDF parsing, Excel ingestion, and OCR from images).

**Why I’m a strong fit for this:**

- **Multi-format data extraction:** I’ve built pipelines that pull from 30+ sources simultaneously — handling HTML (Puppeteer/Playwright for dynamic sites), Excel/CSV parsing, PDF extraction (tabula/pdfplumber), and OCR (Tesseract/Google Vision) for image-based data

- **Data normalization & deduplication:** Experienced with fuzzy matching, schema normalization, and validation layers that catch inconsistencies before they hit your database

- **n8n + custom code hybrid:** For 40-60 sources, I’d architect this as n8n orchestrating the workflow (scheduling, retry logic, alerting) with custom Python/Node modules for the heavy lifting — parsing, OCR, normalization. This gives you visual monitoring + production-grade extraction

- **Nextcloud integration:** Can pipe normalized data directly into Nextcloud-hosted Excel via WebDAV API

- **Error handling & observability:** Dead-letter queues for failed extractions, automatic retry with exponential backoff, Slack/email alerts with source-level granularity, structured logging for audit trails

**About me:** I’m Priyanshu, founder of Evara AI (incubated at IIT Bhubaneswar). We specialize in custom automation and AI systems — code-first approach, zero platform lock-in. Currently based in India, strong English communication, available to start immediately.

**Pricing:** Happy to discuss fixed-price based on a detailed scope call. I typically scope data pipeline projects in phases — MVP with core sources first, then scale.

Would love to hop on a quick call to understand your source landscape and data schema requirements. I can put together a technical proposal within 24 hours of our conversation.

Looking forward to it!

Priyanshu Kumar | Evara AI

14

Hey, this looks like a strong fit. I build production-grade n8n automation systems, have experience with error handling subflows, custom JS nodes, and Supabase/Airtable integrations.

Web scraping pipelines with structured output and validation logic is something I’ve built before. Happy to discuss scope and put together a fixed-price proposal.

Still accepting applications? EMail: [email protected] Website: https://ajbusiness.framer.website

15

Hi @n8ndev_bluru!!! Good day!

Cool project. Multi-source pricing scraping is one of those things n8n handles really well once you get the parsing and validation logic right.

I’ve built scraping workflows that deal with mixed formats — HTML, PDFs, structured data — and for the image-based stuff I’ve used OCR via Google Vision and OpenAI to extract what’s needed. The dedup, retry logic, and alerting side of things is something I enjoy setting up properly so you’re not babysitting workflows at weird hours.

Here’s my portfolio if you want to see how I work: https://iamkenjobs.github.io/

Happy to put together a fixed-price proposal if you want to share more about the scope — how many sources, data volume, timeline, that kind of thing. Or we can just hop on a call. Please send me email [email protected]

Ken

16

Hi there n8ndev_bluru,

This is a really interesting project — vertical pricing intelligence across 40-60 sources is no small task, but n8n is well-suited for it with the right scraping + scheduling architecture.

I’m an n8n automation engineer specializing in data pipelines and AI-powered workflows — structured data extraction and automated processing across multiple sources is right up my alley.

Happy to discuss a fixed-price scope. Here’s a bit of my work: iamkenjobs · GitHub

Feel free to DM me and we can hash out the details.
[email protected]

17

You need a freelancer to automate data extraction from 40-60 online sources, handling HTML, Excel, PDF, and CSV — I’ve built similar multi-source scrapers that normalise messy data into clean pipelines.

Last month I delivered an n8n workflow pulling pricing data from 30+ competitors into a unified dashboard, with automatic format detection and error recovery.

Worth a quick 15-min call this week? Want me to map out the workflow diagram and send it as a first step?

Richard
[email protected]

18

You need a freelancer to automate data extraction from 40–60 online sources, handling HTML, Excel, PDFs, and OCR-based image parsing, then normalising and storing validated output in Nextcloud with duplicate detection and validation rules. I’ve built similar multi-source scraping pipelines in n8n with Python-backed OCR and LLM normalisation layers, consistently delivering clean structured outputs within 48 hours of scope sign-off. Worth a quick 15-min call this week?

Want me to pull a 20-row sample from your target site as a free proof-of-concept?

Richard
[email protected]

19

I started sketching out a node structure for your multi-format ingestion layer — happy to send over the rough flow if it’s useful. I’ve got capacity this week to move quickly.

Richard

20

Hi there,

I’ve reviewed your scope for the Vertical Pricing Intelligence platform, and I’m ready to design a scalable, production-grade data pipeline for your 40–60 sources. I specialize in building high-volume extraction systems in n8n where data integrity and error handling are the priority.

How I will architect your solution:

  • Multi-Source Extraction: I’ll build modular scrapers for HTML, Excel, and PDF parsing using n8n’s native capabilities and custom JS nodes. For OCR, I’ll implement a pipeline (via OpenAI Vision or specialized OCR APIs) to ensure high-accuracy extraction from automotive service images.

  • Data Normalization & Validation: I don’t just “dump” data. I’ll implement a Middle-layer Validation Logic to detect duplicates, normalize currency/pricing formats, and flag outliers before they reach your Nextcloud Excel storage.

  • Fault-Tolerant Design: Given the 40-60 sources, I’ll build Retry & Fallback workflows. If a source changes its layout or a PDF is corrupted, the system will trigger a Slack/Email alert with specific error logs while continuing to process other sources.

  • Nextcloud Integration: I have experience with WebDAV and Cloud API integrations to ensure seamless data delivery to your Nextcloud environment.

Why I’m the right fit:

  • System Thinking: I focus on building a “Data Factory,” not just isolated scripts.

  • Documentation: I provide clean architecture diagrams and a full knowledge transfer session so your team can maintain the system.

  • Timeline: I’m ready to start immediately and work on a fixed-price basis as requested.

Portfolio & Tech Stack: https://mikedevai.netlify.app/ Connect: @hely_chatbots (Telegram)