You will get N8N: AI-Powered Customer Support Automation Engine
Project details
I build practical n8n automation systems designed for real business operations, not just simple workflow demos. What sets this project apart is the combination of AI-assisted support, human review, escalation logic, payment handling, CRM synchronization, and monitoring in one structured pipeline. Instead of automating only one step, I design workflows that handle the full support cycle with better control, visibility, and reliability.
This means faster response times, lower manual effort, cleaner routing, and fewer missed cases. I focus on building automations that are scalable, production-friendly, and aligned with how support teams actually work, with the right balance of automation and human oversight.
This means faster response times, lower manual effort, cleaner routing, and fewer missed cases. I focus on building automations that are scalable, production-friendly, and aligned with how support teams actually work, with the right balance of automation and human oversight.
AI Development Type
Knowledge RepresentationWhat's included
| Service Tiers |
Starter
$300
|
Standard
$700
|
Advanced
$1,200
|
|---|---|---|---|
| Delivery Time | 4 days | 9 days | 16 days |
Number of Revisions | 3 | 5 | 6 |
AI Model Integration | - | - | - |
Detailed Code Comments | - | - | - |
Knowledge Graph | - | - | - |
Model Documentation | - | - | - |
Ontology | - | - | - |
Source Code | - | - | - |
Taxonomy | - | - | - |
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BD
Brian D.
Aug 25, 2025
Full Stack Developer for AI Agent & Automation Projects (LangGraph / n8n / React)
JL
Jerina Amber L.
Aug 22, 2025
Next.js & TypeScript Developer for Vercel's Chat SDK Integration
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Dongjoo K.
Aug 20, 2025
HIPAA-Compliant Medspa Platform Development
Very cooperative and supportive.
CC
Carmen C.
Jul 9, 2025
Front-End Developer for Web Platform
Thank you!
LK
Lukas K.
Mar 7, 2025
Mobile app Andorid / ios
Perfect perfect perfect !!! Awsome response dast work and this guy is thinking what will be next and prepare it for next stages. Tahnk you very mcuh
About Pintu
AI Engineer | Agentic AI | Automation | RAG | n8n | LangChain
100%
Job Success
Surat, India - 1:28 am local time
My work sits at the intersection of AI engineering and automation architecture: designing multi-agent systems, RAG pipelines, LLM-powered backends, and workflow automation that replace manual operations with intelligent, reliable processes.
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◉ WHAT I BUILD:-
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► AI Agents & Multi-Agent Systems
- Autonomous agents with tool use, memory, and self-correction (LangGraph)
- Supervisor / worker agent architectures for complex, multi-step tasks
- LangChain-powered pipelines with routing, retrieval, and structured output
- Human-in-the-loop flows with approval steps and fallback logic
► RAG & Knowledge Systems
- Production RAG pipelines: chunking strategy, hybrid search, re-ranking
- Vector database integration (Pinecone, Weaviate, pgvector, Chroma)
- Document intelligence: extraction, classification, summarization at scale
- Semantic search layers embedded into existing products
► AI Automation & Workflow Orchestration
- n8n + LLM workflows that replace manual operations end-to-end
- Intelligent intake, triage, routing, and notification pipelines
- AI-powered data enrichment, lead scoring, and document processing
- Zapier / Make → n8n migrations with AI nodes added
► Full-Stack AI Frontend (React / Next.js)
- AI chat interfaces with streaming responses (SSE / WebSockets)
- Real-time AI dashboards: live agent status, pipeline logs, cost tracking
- AI copilot UIs embedded inside existing SaaS products
- Next.js AI-first web apps with server actions + edge functions
- Component libraries built on top of Vercel AI SDK, shadcn/ui, Tailwind
► LLM Integration & API Engineering
- OpenAI, Anthropic Claude, Gemini, Mistral, Llama (self-hosted) integrations
- Function calling, structured output, tool use, and multi-modal pipelines
- Prompt engineering, eval frameworks, and cost optimization
- FastAPI / Node.js backends serving AI features at production scale
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◉ FULL AI TECH STACK:-
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Orchestration: LangChain · LangGraph
LLMs: OpenAI GPT-4o · Anthropic Claude · Google Gemini
Frontend: React.js · Next.js · Typescript · Tailwind CSS
Backend: Python · FastAPI · Flask · PostgreSQL · Redis · Docker
Deployment: AWS · GCP · Vercel · Docker
Vector DBs: Pinecone
Automation: n8n
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◉ WHO I WORK WITH:-
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- SaaS companies embedding AI into their products
- Startups building AI-first platforms from scratch
- Enterprises automating internal operations with LLMs
- Technical founders who need an AI engineer, not a prompt wrapper
- Agencies building white-label AI products for clients
Let's scope your project - message me with what you're building.
Steps for completing your project
After purchasing the project, send requirements so Pintu can start the project.
Delivery time starts when Pintu receives requirements from you.
Pintu works on your project following the steps below.
Revisions may occur after the delivery date.
Workflow Planning
Map the automation logic, integrations, escalation rules, and review flow.
n8n Build & Integration
Build the n8n workflow with AI replies, CRM sync, payment logic, and routing.