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I built a custom AI Voice Agent for a service-based business to automate their appointment booking process. The system handles inbound/outbound calls, qualifies customers, and manages scheduling without any human intervention.
The Technical Challenge
The goal was to create a "robust" agent that could handle natural human speech patterns including stammers or mid-sentence changes while maintaining the conversational flow. I needed to bridge the gap between high-fidelity voice synthesis and real-time database management.
The Solution & Workflow
Voice & Logic: Integrated ElevenLabs for realistic vocal performance and Retell AI (or similar) for low-latency conversational handling.
Automation Engine: Built complex workflows in n8n to process the data gathered during the call.
Real-time Integration: The system automatically cross-references and updates Google Calendar, sending instant confirmations to both the client and the customer.
The Results
100% Automation: Successfully moved the client from manual phone bookings to a fully autonomous system.
Error Handling: Programmed the agent to stay on track even when users provide vague or self-correcting input.
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Built ScopeFlow leveraging heavily on Anything!
_> Answer 5 questions → get a board-room-ready AI project brief in 60 seconds.
_> Executive summary, phased timeline, investment range, PDF export — all AI-generated.
_> White-label ready out of the box. Try it free 👇
🔗; Link to app
_> Demo video
_> X post
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Hi, I’m Vlad — an End-to-End AI Engineer helping businesses turn AI ideas into production-ready applications.
I build LLM apps, RAG systems, private knowledge assistants, NLP pipelines and workflow automation tools that connect to real data, APIs and existing business workflows.
Open to AI application development, backend + AI integration and automation projects.
n8n + AI Vision — Automated Invoice Processing (PDF → ERP)
Supplier invoices arrive as PDFs in a shared inbox. AI Vision reads each invoice, extracts header, line items and
totals, validates the math, and posts the entry directly to the ERP — SAP, NetSuite, Dynamics, Odoo or Sage.
Exceptions only escalate when truly needed.
The problem
Accounts payable was bottlenecked by inbox triage. Someone had to open every supplier invoice PDF, retype headers,
line items, VAT and totals into the ERP, and chase the supplier when numbers didn't match. Slow, error-prone, and the
backlog built up every month-end.
What I built
A fully automated invoice-to-ERP pipeline that handles the full document flow without a human touch unless something
is genuinely off:
Inbox watcher detects new invoices in the AP shared mailbox.
AI Vision (GPT-4) parses the PDF — supplier data, invoice number, dates, line items, subtotals, VAT, totals.
Validation layer checks the math, matches the supplier against the master vendor list, flags duplicates and missing fields.
ERP posting — entry written directly into SAP / NetSuite / Dynamics / Odoo / Sage via official API or DB connector.
Exception queue — only documents that fail validation hit a human, with the reason pre-explained.
The stack
n8n · GPT-4 Vision (OCR + structured extraction) · ERP connectors (SAP / NetSuite / Microsoft Dynamics / Odoo / Sage)
· Validation engine · Slack/email exception alerts · Audit-ready logs.
Outcome
+400 invoices/month processed end-to-end without human entry
0 typing errors on posted entries — the AI doesn't fat-finger numbers
Month-end closes faster — the AP backlog stops being a bottleneck
Same-day visibility on flagged exceptions
Want something similar?
The same engine handles purchase orders, delivery notes, contracts, customer onboarding forms — anywhere a structured
document arrives by email and gets retyped into a system today.
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