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Built an AI-powered recruitment automation workflow using Make.com and Airtable to automate candidate intake, email confirmations, recruiter notifications, interview scheduling, and follow-up processes.
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AI Assistant Using Your Business Knowledge Base — RAG on Your Documents
THE PROBLEM
Q&A bots break down when knowledge lives in documents: a 100-page manual has no "questions" to match, it can't fit into a prompt, and generic chatbots hallucinate instead of admitting what they don't know.
THE SOLUTION
A RAG (Retrieval-Augmented Generation) knowledge base: documents are split into meaningful chunks, embedded into a vector index, and the assistant answers from the right sections — by meaning, not keywords.
Any format as-is: PDF, DOCX, TXT, Markdown — 100+ pages is fine
Answers grounded in YOUR documents — it says "I don't have that information" rather than inventing
Source references — every answer shows which document and section it came from
Runs on your infrastructure — documents never leave your control
One command to re-index after updating documents — documented, no programmer needed
LIVE DEMO
Ask it about my products, pricing, deployment and support — it answers from 6 real documents with sources:
https://kb-assistant-demo.dvc-ai.workers.dev
The 'I don't have that information' line is the part most RAG builds skip, and it's the one that matters. How do you set the cutoff? On mine, a fixed similarity threshold broke once I filtered results by user role. Scores shifted and it refused questions it could answer.
Automated a manual Google Sheets → Slack workflow to eliminate repetitive data entry and give the team instant notifications.
Previously, new data had to be manually checked, processed, and shared across the team — slow and easy to miss. I built a Make.com scenario that:
Watches Google Sheets for new/updated rows
Processes and routes the data through a router based on conditions
Creates corresponding Trello cards for task tracking
Logs processed records back to Google Sheets
Sends real-time Slack notifications so the team is instantly updated
Result: What used to be manual checking and updating is now fully automated — saving hours weekly and removing room for human error.
Tools: Make.com, Google Sheets, Trello, Slack
wow love this
Built an AI-powered Slack bot that manages inventory and orders directly from chat — no spreadsheet switching required.
The team needed a faster way to check stock and log orders without leaving Slack. I built a Make.com scenario that:
Watches Slack for new messages
Passes the message to a Make AI Agent, which interprets the request (check stock, place an order, update inventory)
The AI Agent searches inventory, creates orders, or updates stock levels in Google Sheets depending on intent
Sends the answer straight back to Slack as a reply
Result: The team can now manage inventory and orders with a simple Slack message — the AI Agent handles the logic and Google Sheets stays updated automatically, with zero manual lookups.
Tools: Slack, Make AI Agents, Google Sheets (built on Make.com)
