Imagine knowing which buyer is serious about purchasing the moment they submit your form.
They get lost because nobody qualifies them fast enough.
When a buyer fills a form, someone still has to open the responses, read everything, decide if the lead is serious, and then follow up. By the time that happens, the buyer is often already speaking with another agent.
To solve this, I built a simple AI Buyer Qualification Workflow.
Now the moment a buyer submits a Typeform:
• The lead details are captured automatically
• AI analyzes the responses and classifies the lead based on buying timeline
• 🔥 Hot Lead — Buying immediately
• 🟠 Warm Lead — Planning within 1–3 months
• 🔵 Cold Lead — Planning within 4–6 months
The system then:
• Saves the lead and score into Google Sheets
• Sends a priority email alert through Gmail with all the lead details
This means agents instantly know which leads require immediate follow-up and which ones can be nurtured.
No manual sorting.
No delays.
Just clear and prioritized leads ready for action.
Feel free to explore this template and see how it works with real data:
https://lnkd.in/gH8NfC5Y
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
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.