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I developed PRE-GEN detect, a standalone visual jailbreak detection service designed to prevent AI video generation platforms like Buddian from outputting copyrighted or protected IP.
Multimodal AI Integration: Integrated the TwelveLabs Pegasus model to stream and analyze raw MP4 videos, automatically extracting comprehensive physical descriptions of generated subjects.
Automated IP Arbitration: Engineered a strict arbitration pipeline utilizing OpenAI models, Pydantic, and structured JSON outputs to act as a definitive judge between the visual extraction and the protected Prampta IP registry.
Secure Media Extraction: Built a custom URL resolution and scraping module using Python, Requests, and BeautifulSoup to parse client-side rendered video pages, strictly validating against non-public IPs to prevent server-side request forgery (SSRF) attacks.
Rapid Prototyping: Built and containerized the entire pipeline under hackathon constraints, deploying a lightweight, responsive user interface via Streamlit and Docker.
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I cooked two versions for branding. 🍳
One was the original recipe.
The other got a full revamp.
Same idea, different treatment and now I genuinely can't decide which one works harder.
11 voted
46%
13 voted
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Closed
Original cut works for me
AI-Powered Client Enquiry Automation
Project Overview:
I built an AI-powered client enquiry automation workflow using Zapier, Google Forms, Google Sheets, AI by Zapier, Gmail, and Google Calendar.
The goal was to automate the initial handling of client enquiries from receiving the enquiry to understanding the client's needs, sending an acknowledgement, and creating a follow-up task.
The Problem:
Managing client enquiries manually can be repetitive and time-consuming. Each new enquiry needs to be reviewed, categorized, summarized, responded to, and followed up.
Without a structured process, it's easy for enquiries to be delayed or follow-ups to be missed.
The Solution:
I designed a workflow that automates these repetitive administrative tasks while using AI to analyze the information provided by the client.
The automation follows this process:
Client submits enquiry
↓
Google Sheets captures the enquiry
↓
AI analyzes the enquiry
↓
Gmail sends an acknowledgement
↓
Google Calendar creates a follow-up
How It Works:
1. Enquiry Collection.
The client submits their details and enquiry through a Google Form. The information is automatically recorded in Google Sheets.
2. AI Analysis.
AI by Zapier reviews the enquiry and extracts key information such as the service category, priority, concise summary of the client's needs, and recommended next action.
This eliminates the need to manually review every enquiry just to determine what it is about and how it should be handled.
3. Automated Client Response.
After the enquiry is processed, Gmail automatically sends the client an acknowledgement, ensuring they receive a timely response.
4. Follow-Up Management.
The workflow creates a Google Calendar follow-up, helping ensure that the enquiry doesn't get lost after the initial response.
Result:
The completed workflow turns a manual enquiry process into a structured automated system:
Capture → Analyze → Respond → Follow Up
The key improvement is the use of AI as a decision-making layer, rather than simply moving information from one application to another.
This demonstrates how AI automation can reduce repetitive administrative work, improve response consistency, and help businesses stay organized with client enquiries.
Tools Used:
Zapier | AI by Zapier | Google Forms | Google Sheets | Gmail | Google Calendar
Skills Demonstrated:
AI Automation • Workflow Design • Administrative Automation • AI Prompting • Client Enquiry Management • Email Automation • Calendar Automation • Process Optimization
Really clean workflow, Ann. The Capture → Analyze → Respond → Follow Up structure makes the business value immediately clear. One useful next layer could be an exception route for urgent or low-confidence enquiries, so AI handles the routine cases while anything uncertain...
Created a demo AI automation workflow for lead capture and follow-up. The workflow captures leads through Google Forms, stores data in Google Sheets, sends automated email responses, updates a CRM, and notifies the team through Slack. This project demonstrates my skills in AI automation, workflow design, integrations, and business process automation.
Lead capture and follow-up are excellent areas for practical AI automation because missed responses directly affect revenue. A useful system should capture the enquiry, understand the lead’s intent, update the CRM, notify the right team member, and trigger appropriate follow-ups...