Piero Savastano
Founder at Cheshire Cat AI
Greater Rome Metropolitan Area Italy
Summary
🤩
Rockstar🎓
Top SchoolPiero Savastano is a founder and data scientist with 12 years of hands-on experience building AI systems and teaching the next generation of practitioners. He started experimenting with neural networks at 19—implementing a Hopfield network from scratch—and today leads Cheshire Cat AI, focusing on agent orchestration and vector-backed conversational services. His open-source work includes developing a WebSocket-enabled AI agent microservice that integrates Qdrant for vector memory and GPT-3 for real-time chat, reflecting practical expertise in vector databases and production-grade back-end engineering. Piero pairs an academic background in cognitive psychology, neurophysiology and AI with industry experience consulting for Sony and lecturing at design and game academies, bridging human-centered insight and scalable architectures. Based in the Greater Rome area, he combines researcher instincts with entrepreneurial drive to turn experimental models into deployable products.
12 years of coding experience
5 years of employment as a software developer
Scholarship Artificial Intelligence, Scholarship Artificial Intelligence at E.Co.N.A. Research CenterScholarship Neurophysiology, Scholarship Neurophysiology at University of TübingenMaster Psichology and Engineering, Master Psichology and Engineering at Sapienza Università di Roma
English, Italian
Github Skills (14)
fastapi10
agent10
openai10
python10
langchain10
qdrant10
llm10
client-websocket9
websocket-client9
ai9
websocket9
websockets-client9
docker4
dockers4
Programming languages (14)
Github contributions (5)
cheshire-cat-ai/core
Feb 2023 - Mar 2023
AI agent microservice
Role in this project:
Back-end Developer
Back-end DeveloperContributions:72 reviews, 73 commits, 510 PRs in 1 month
Contributions summary:Piero primarily contributed to the development of a web-based AI agent microservice. Their work involved creating a minimal web server with WebSocket functionality for real-time communication. They integrated vector memory containers using Qdrant for embedding and searching, demonstrating knowledge of vector databases. Further contributions included incorporating OpenAI's GPT-3 model for chat functionality and agent orchestration.
agentaiassistantbotbot-framework
pieroit/corso_ml_python_youtube_pollo
Sep 2019 - Sep 2020
Materiale del corso di machine learnign in python su Youtube https://www.youtube.com/watch?v=U78wETHkBKU&list=PLa-sizbCyh93evwIevvnjWFEH94N5giIG
Contributions:26 commits, 19 pushes, 1 branch in 1 year
plapythonmachine-learningyoutubecorso
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