You will get a Production n8n Workflow with Error Handling & Full Handover
Project details
Most automation projects fail the same way: they work in a demo and break the first week they hit real data. Missing fields, API timeouts, duplicate records, edge cases nobody scoped.
I build n8n workflows that survive that. Error handling, retries, logging, and conditional branching are part of the build, not an afterthought — because a workflow that fails silently is worse than no workflow.
I have four systems running in production, including an n8n pipeline that scores inbound leads across 15+ signals, writes to a live CRM, assigns drip campaigns, and fires real-time alerts on high-value leads. It has processed over 1,100 leads.
I work in two areas only: n8n workflow automation and agentic RAG systems. That focus is deliberate — it means I've hit most of the failure modes before.
You get a working system, written documentation, and a recorded handover walkthrough, so your team can run and modify it without me.
I build n8n workflows that survive that. Error handling, retries, logging, and conditional branching are part of the build, not an afterthought — because a workflow that fails silently is worse than no workflow.
I have four systems running in production, including an n8n pipeline that scores inbound leads across 15+ signals, writes to a live CRM, assigns drip campaigns, and fires real-time alerts on high-value leads. It has processed over 1,100 leads.
I work in two areas only: n8n workflow automation and agentic RAG systems. That focus is deliberate — it means I've hit most of the failure modes before.
You get a working system, written documentation, and a recorded handover walkthrough, so your team can run and modify it without me.
AI Algorithms
Large Language ModelAI Applications
AI Chatbot, AI-Enhanced Classification, Natural Language UnderstandingAI Development Language
PythonAI Tools
GitHub Copilot, StreamlitAI Models
ChatGPTWhat's included
| Service Tiers |
Starter
$1,500
|
Standard
$4,000
|
Advanced
$8,000
|
|---|---|---|---|
| Delivery Time | 7 days | 21 days | 35 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.
Monthly Maintenance & Monitoring
+$500Frequently asked questions
About Girish Kumar
n8n Automation & Agentic RAG Engineer | LangGraph, MCP, Python
Bengaluru, India - 10:22 am local time
unattended — not demos, not prototypes.
Most AI automation projects fail at the same place: they work in a
demo and break on real data. I've shipped four systems currently
running in production, including an n8n lead-scoring pipeline
processing 15+ signals into a live CRM, and an offline-capable legal
document RAG chatbot with a local/cloud model toggle for
air-gapped environments.
WHAT I BUILD
- n8n workflow automation — multi-step pipelines with error handling,
logging, retries, and human-in-the-loop approval gates
- Agentic RAG — retrieval + tool-calling + orchestration with LangGraph,
ChromaDB and other vector stores, sentence-transformers
- n8n as an MCP server with Claude as MCP client — the setup that lets
an LLM safely trigger your real business workflows
HOW I WORK
Fixed-scope, fixed-price packages. You get a working system, full
documentation, and a handover walkthrough — so you're not dependent
on me to run it.
Stack: n8n, LangGraph, Python, FastAPI, Docker, ChromaDB,
sentence-transformers, GCP, Streamlit.
Certified: IBM AI Engineering
I do not take on: generic ML model training, data labeling, or
staff-augmentation PM roles.
Let’s Work:
Currently taking on: production builds, agency white-label delivery,
and ongoing retainers.
If you have a workflow that breaks under real data — or a RAG system
that works in testing and fails in front of users — send me the
details and I'll tell you straight whether I'm the right fit.
Steps for completing your project
After purchasing the project, send requirements so Girish Kumar can start the project.
Delivery time starts when Girish Kumar receives requirements from you.
Girish Kumar works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery and scope confirmation
We review your process together, confirm the trigger points, edge cases, and success criteria. You get a written scope before any building starts.
Workflow build
I build the core workflow in n8n with all integrations connected, then layer in error handling, retries, and logging so it survives real-world data.