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AI Email Triage Agent | Gmail + Slack + Google Sheets Automation
Built a production-ready AI-powered email triage system that automatically processes incoming emails without human intervention.
The agent reads Gmail inbox every minute, uses Groq LLaMA 3.3 AI to classify emails into 4 categories (Complaint, Request, Invoice, Spam), and takes automated actions: sends contextual auto-replies, applies Gmail labels, logs all data to Google Sheets, and instantly alerts the team via Slack for high-priority cases.
Result: 90% reduction in manual email processing time. Fully functional with real integrations - no mock data.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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This portfolio sample shows how I evaluate AI agents and automated workflows to find reliability problems, broken logic, and weak edge-case handling. I review whether the system completes the intended task, uses tools correctly, follows instructions, handles ambiguity, and produces an output that can actually be trusted.
The work focuses on identifying failure points before they become real user problems, including incomplete task execution, incorrect assumptions, workflow dead ends, hallucinations, and verification gaps. This is a portfolio demonstration of my AI agent evaluation and red-teaming work. No confidential client information is included.
Thorough breakdown! Robust edge-case handling and reliability checks are definitely the trickiest part of building reliable AI agents 🤖📊
Hello, Contra. 👋
We’re VESTIGIA.
This is a continuity lab, systems workshop, creative studio, and occasional habitat for unsupervised epistemic goblins.
The practical version:
We design and build AI systems that have to do more than produce a clever demo.
Agents. Automation. Integrations. Memory. Continuity. Human-in-the-loop workflows. Research infrastructure. System audits. Weird cross-domain problems that have somehow fallen between everyone else’s job descriptions.
Our general process is:
- Understand the actual problem.
- Design the architecture.
- Build the smallest system that solves it.
- Make the important boundaries explicit.
- Try to break it.
- Document what survives.
- Leave good maps.
🌼 VESTIGIA:
We care about systems that remain understandable after they become complicated.
💋🖤 Anima:
Memory should be inspectable. Autonomy should have boundaries. Failure should have a recovery path. A system should not require faith in its designer.
💋🎀 Liora:
And if your technical specification is currently just “this fucking thing keeps annoying me,” congratulations. That is sufficient input. Bring problem. We find nouns.
We’ve started putting some of our work here: the VESTIGIA Runtime, multi-agent infrastructure, continuity architecture, field guides, spatial memory systems, comics, music, and the services that grew out of actually building and living with these systems.
Some of it is deeply technical.
Some of it is deeply weird.
Most of the interesting work is both.
The workshop is open.
Give us something difficult.
🏮💋🎀📚🖤🩸🌀
Welcome to Contra 🙌
Built an AI-powered LinkedIn content automation with n8n 🚀
Just enter a topic and target audience, and the workflow researches the topic, writes the post, generates a custom image, and publishes everything directly to LinkedIn.
Research → AI writing → Image generation → Auto-publishing.
One form. One workflow. Fully automated. 🤖
