🚀 Automated AI Document Processing & ATS Pipeline (n8n)

Project Summary Replaced a manual candidate screening process with a fully automated, n8n-orchestrated backend pipeline. The system automatically intercepts incoming applications, uses OpenAI to analyze documents, updates databases, and triggers client communication—cutting manual data entry down to zero. The Outcome & Business Value

Eliminated Manual Data Entry: Automated 100% of resume parsing, document conversions (Docs to PDF), and data extraction tasks.

Instant Candidate Screening: Integrated an OpenAI Chat Model Decider to evaluate incoming resumes against job descriptions in real-time with zero human delay.

Automated Sync & Follow-Ups: Automated instant logging to Google Sheets and launched immediate multi-path email responses based on candidate status.

How It Works (System Architecture)

Phase 1 (Ingestion & Extraction): Captures files via webhooks/emails ➡️ Cleans data via custom code nodes ➡️ Parallel-processes files to extract raw text ➡️ Uses AI structured parsing to match applicants to open roles.

Phase 2 (Database & Delivery): Routes structured applicant data ➡️ Upserts matching rows into a centralized tracking database ➡️ Triggers dynamic conditional emails back to candidates.

Good CRM reporting is only as reliable as the data behind it.

When I started working with Momentum AMP, one of the biggest challenges was inconsistent HubSpot data, which made it difficult for the team to fully trust its reporting.

What initially started as a data analytics engagement developed into a much broader HubSpot development and operations partnership.

I introduced daily data-quality monitoring to identify and resolve issues before they could affect reporting, while also building and improving automation across the CRM.

The work expanded into sales commission workflows, weighted deal assignment, customer success processes, reporting improvements and wider operational automation. I also supported projects including Stripe data cleanup and a Gemini AI integration.

For the SCC team specifically, I automated processes around lead rotation, outreach, post-mortem tracking and email distribution — reducing the amount of manual work required across their day-to-day operations.

The engagement has now covered more than 390 CRM tasks, with data-quality checks running every working day since September 2024.

The result is a HubSpot environment with more reliable data, stronger automation and reporting the team can actually trust when making decisions.

For me, this project shows why CRM optimisation starts with the fundamentals. You can build sophisticated workflows and dashboards, but if the underlying data isn’t reliable, the rest of the system can’t deliver its full value.