Alok Kumar
I am a Principal Software Engineer based in Ireland with a deep passion for AI and emerging technologies. With extensive experience in designing and implementing scalable software solutions, I focus on leveraging artificial intelligence to solve real-world problems. I enjoy exploring innovative applications of AI, from intelligent automation to data-driven insights, and I’m dedicated to building systems that are both efficient and impactful.
Templates by Alok Kumar
Website content chatbot with Pinecone, Airtable & OpenAI for RAG applications
This n8n workflow shows how to extract website content, index it in Pinecone, and leverage Airtable to power a chat agent for customer Q&A. Use cases include: Building a knowledge base from your website. Creating a chatbot that answers customer queries using your own site content. Powering RAG workflows for FAQs, support docs, or product knowledge. --- How it works Workflow starts with a manual trigger or chat message. Website content is fetched via HTTP Request. The HTML body is extracted and converted into clean Markdown. Text is split into chunks (~500 chars with 50 overlap) using the Character Text Splitter. OpenAI embeddings are generated for each chunk. Content and embeddings are stored in Pinecone with namespace separation. A Chat Agent (powered by OpenAI or OpenRouter) retrieves answers from Pinecone and Airtable. Memory buffer allows multi-turn conversations. A billing tool (Airtable) provides dynamic billing-related answers when needed. --- How to use Replace the sample website URL in the HTTP Request node with your own domain or content source. Update Normalize code based on markdown content output to remove noise. Adjust chunk size in the Text Splitter for your website markdown output. In this example, the Character Text Splitter with separator worked really well. Always check the Markdown output to fine-tune your splitting logic. Update Pinecone namespace to match your project. Customize the Chat Agent system prompt to fit your brand voice and response rules. Connect to your own Airtable schema if you want live billing/payment data access. --- Requirements OpenAI account (for embeddings + chat model). Pinecone account (vector DB for semantic search). Airtable account (if using the billing tool). (Optional) OpenRouter account (alternative chat model provider). n8n self-hosted or cloud. --- Need Help? Ask in the n8n Forum! Happy Automating! 🚀
By Alok KumarGenerate PRDs and test scenarios with GPT/Claude and PDF export
📒 Generate Product Requirements Document (PRD) and test scenarios form input to PDF with OpenRouter and APITemplate.io This workflow generates a Product Requirements Document (PRD) and test scenarios from structured form inputs. It uses OpenRouter LLMs (GPT/Claude) for natural language generation and APITemplate.io for PDF export. Who’s it for This template is designed for product managers, business analysts, QA teams, and startup founders who need to quickly create Product Requirement Documents (PRDs) and test cases from structured inputs. How it works A Form Trigger collects key product details (name, overview, audience, goals, requirements). The LLM Chain (OpenRouter GPT/Claude) generates a professional, structured PRD in Markdown format. A second LLM Chain creates test scenarios and Gherkin-style test cases based on the PRD. Data is cleaned and merged using a Set node. The workflow sends the formatted document to APITemplate.io to generate a polished PDF. Finally, the workflow returns the PDF via a Form Completion node for easy download. ⚡ Requirements OpenRouter API Key (or any LLM) APITemplate.io account 🎯 Use cases Rapid PRD drafting for startups. QA teams generating test scenarios automatically. Standardized documentation workflows. 👉 Customize by editing prompts, PDF templates, or extending with integrations (Slack, Notion, Confluence). Need Help? Ask in the n8n Forum! Happy Automating with n8n! 🚀
By Alok KumarSupabase storage tutorial: Upload, fetch, sign & list files
Learn Supabase Storage Fundamentals with n8n This template demonstrates how to integrate Supabase Storage with n8n for uploading, fetching, generating temporary signed URLs, and listing files. It’s a beginner-friendly workflow that helps you understand how to connect Supabase’s storage API with n8n automation. --- Who it’s for Developers and teams new to Supabase who want a hands-on learning workflow. Anyone looking to automate file uploads and retrieval from Supabase Storage. Educators or technical teams teaching Supabase fundamentals with practical demos. --- How it works Upload File – A user uploads a file through an n8n form, which gets stored in a Supabase storage bucket. Fetch File – Retrieve files by providing their filename. Temporary Access – Generate signed URLs with custom expiry for secure file sharing. List Objects – View all stored files in the chosen Supabase bucket. --- How to set up Create a Supabase account and set up a project. Create a bucket in Supabase (e.g., test-n8n). Get your Project URL and Anon Key from Supabase. In n8n, create a Supabase API Credential using your keys. Import this workflow and connect it with your credentials. Run the forms to test file upload, retrieval, and listing. --- Requirements A Supabase project with storage enabled. A configured Supabase API Credential in n8n. --- Customization Change the bucket name (test-n8n) to your own. Adjust signed URL expiry times for temporary file access. Replace Supabase with another S3-compatible storage if needed. Extend the workflow with notifications (Slack, Email) after file upload. --- 📝 Lessons Included Lesson 1 – Upload file to Supabase storage. Lesson 2 – Fetch file from storage. Lesson 3 – Create a temporary signed document with expiry. Lesson 4 – List all items in Supabase storage. --- 🔑 Prerequisites Supabase account + project. Project URL and API Key (Anon). Bucket created in Supabase. Policy created to allow read/write access. n8n with Supabase API credentials configured.
By Alok KumarAutomate document approvals with multi-level workflows using Supabase & Gmail
Multi-Level Document Approval & Audit Workflow This workflow automates a document approval process using Supabase and Gmail. --- Who it’s for Teams that need structured multi-level document approvals. Companies managing policies, contracts, or proposals. Medical document need multiple lavel of review and approval. --- How it works Form Trigger – A user submits a document via the form. Supabase Integration – The document is saved in the documents table. Supabase Storage – The document is saved in the bucket. Workflow Levels – Fetches the correct approval level from workflow_levels. Assign Approvers – Matches approvers by role from the users table. Approval Record – Creates an approvals record with a unique token and expiry. Email Notification – Sends an email with Approve / Reject links. Audit Logs – Records every approval request in audit_logs. Repeat - repeat the flow till all the aproval level is comepted --- How to set up Configure your Supabase credentials. Create tables as per data model given. Create a storage bucket in Supabase Storage. Connect your Gmail account. Adjust approval expiry time (48h default). Deploy and test via the Form Trigger. --- Customization Add multiple approval levels by chaining workflow_levels. Replace Gmail with Slack, Teams, or another notification channel. Adjust audit logging for compliance needs. Update the endpoint http://localhost:5678/webhook-test/ based on instance and env (remove test if you run in prod) Update the bucket name. --- Important steps Form Submit Triggered when by submiting form Captures form parameters: Title (Document Title) Description (Document Description) file (Document need for approval) Webhook Entry Point Triggered when an approver clicks the Approve or Reject link in email. Captures query parameters: token (approval token) decision (approved/rejected) --- Approval Data Retrieval & Update Fetch approval record from Supabase (approvals) using token. Update approval status: Approved → moves to next workflow level or final approval. Rejected → document marked as rejected immediately. Records acted_at timestamp. --- Decision Check IF Node checks whether the decision is approved or rejected. Reject Path → Update document status to Rejected in documents. Approve Path → Continue workflow level progression. --- Workflow Level Progression Fetch details of the current workflow level. Identify the next level (workflowlevels) based on levelnumber. ✅ If Next Level Exists: Retrieve approvers by role_id. Generate unique approval tokens. Create new approval records in approvals. Send email notifications with approval/reject links. ❌ If No Next Level (Last Level): Update document status to Approved in documents. --- Audit Logging Every approval action is logged into audit_logs table: document_id action (e.g., approval_sent, approved, rejected) actor_email (system/approver) details (workflow level, role info, etc.) --- 📨 Email Template Approval request email includes decision links: html <p>Please review the document:</p> <p> <a href="http://localhost:5678/webhook-test/doc-approval?token={{$json.token}}&decision=approved">✅ Approve</a> | <a href="http://localhost:5678/webhook-test/doc-approval?token={{$json.token}}&decision=rejected">❌ Reject</a> </p> Happy Automating! 🚀
By Alok Kumar