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I recently discovered Amphi (Amphi AI) and was fascinated by its unique Pandas-based approach to data engineering. Amphi.ai stands for “duality” and takes a unique (GUI↔Code) approach to data transformation.
I had the opportunity to speak with the founder Thibaut Gourdel, who shared a demo and his exciting vision for the platform:
Demo: lnkd.in/gxDjc4xN
Post: lnkd.in/gnr5miTW
Amphi: amphi.ai/
GitHub: lnkd.in/e7ANZgqA
Check out Amphi, give it a star on GitHub, and keep an eye on its progress!
Topics
[00:00:00] Start
[00:00:05] Introduction and Welcome
[00:00:10] Meet Thibaud: Founder of Amphi
[00:00:48] What is Amphi?
[00:02:21] Amphi's Go-to-Market and Deployment
[00:03:28] Live Demo of Amphi
[00:04:07] Building and Running Pipelines
[00:05:43] Amphi's Connectors and Community Contributions
[00:07:23] Olympics Data Use Case
[00:09:29] Future Plans and Integrations
[00:17:11] The Role of LLMs and Agents in ETL
[00:19:22] Exploring the Future of Integration Tools
[00:19:56] Open Source Agents and Ecosystem
[00:20:35] Traction and User Adoption
[00:21:51] Monetization Strategies and SaaS Potential
[00:23:06] Journey from Enterprise to Entrepreneurship
[00:25:33] Vision for the Future of Amphi
[00:35:12] Comparing Amphi with Apache NiFi
[00:36:25] Final Thoughts and Call to Action
Discover Amphi.ai, the game-changing low-code Python-based ETL tool for structured and unstructured data. Join us as we sit down with Thibaut, the founder, to explore how Amphi.ai accelerates data pipeline development, generates native Python code, and empowers data practitioners. Learn about its visual interface, local processing for privacy, and AI integration capabilities.
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