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AI Tinkerers - Seattle
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Team

Xpertli

Project Concept

Personal AI agent to help expert consultants filter and automatically apply for consulting gigs based on their proprietary knowledge.

Entry

Status: Submitted

Last saved: May 18 at 2:07 PM PDT

Team Roster

Message board not available for this team yet.

Adam Burgh Team Lead RSVP Approved

Founder and CEO at We Build With AI
Vibe coder extraordinaire. Set up Crew AI agents with Open AI and provided test data.
Adam Burgh is a seasoned tech industry leader with a proven track record of scaling and leading global companies and startups. Currently serving as the Founder and CEO of We Build With AI, Adam's expertise lies in innovation and growth within the tech sector. With a background in product management, strategy, analytics and marketing, Adam's technical acumen is complemented by his strong leadership skills. He is currently open to advisory or fractional executive roles, or seeking potential technical co-founders interested in using AI to create a knowledge discovery and sharing platform for employees to securely access their company’s proprietary documents and information.
Leadership, scaling startups, product innovation and prioritization, growth marketing and strategy.
Education platform to help everyone build with AI, regardless of formal technical training. Expert network of external and internal human experts as well as expert agents. Knowledge discovery and sharing platform for employees to securely access their company’s proprietary documents and information.

Chuci Chen RSVP Approved

Senior Applied scientist at Amazon
Real coder extraordinaire. Created Google email triggers and fallback code leveraging Open AI if crews fail.
I have 7-year Working Experience in building end-to-end production pipeline in Data & Applied science field. I have mainly focused on Predictive Machine Learning, Time Series Prediction and Causal Inference Framework, aiming to build accurate and reasonable models that could be easily scaled to multiple territories.
Machine Learning, LLM, RAG, Agent