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SVP Investor and Public Relations
May 2025
Flex (Reg. No. 199002645H) is the global manufacturing partner of choice that helps leading brands design, build, and manage products that improve the world. For more information, visit flex.com.
We love to hear your thoughts, comments and ideas so feel free to like, share and comment away. Any question or opinion is good to go as long as it is respectful and falls within the scope of this page. Derogatory comments, spam and unsolicited selling are not welcome here and such posts will be removed.
Board Member
May 2023
PSYKHE AI is the infrastructure layer for taste. We profile every product psychographically - encoding the traits, contexts, and emotional tones that drive preference - and match them to people in real time, without prompts, search, or prior history.
On the product side: every item gets a structured representation agents and models can reason over. Aesthetic identity, personality resonance, use context, emotional tone - all machine-readable, all grounded.
On the user side: we infer psychographic identity from behavioral signals as it forms, so the system works from the first session.
The result is a decision layer that predicts what each person will want - across categories, contexts, and interfaces. Agent, search surface, feed, or API.
Experience · 2 entries
All (2)
Investments (2)
Board (1)
2025
SVP Investor and Public Relations
May 2025
Flex (Reg. No. 199002645H) is the global manufacturing partner of choice that helps leading brands design, build, and manage products that improve the world. For more information, visit flex.com.
We love to hear your thoughts, comments and ideas so feel free to like, share and comment away. Any question or opinion is good to go as long as it is respectful and falls within the scope of this page. Derogatory comments, spam and unsolicited selling are not welcome here and such posts will be removed.
2023
Board Member
May 2023
PSYKHE AI is the infrastructure layer for taste. We profile every product psychographically - encoding the traits, contexts, and emotional tones that drive preference - and match them to people in real time, without prompts, search, or prior history.
On the product side: every item gets a structured representation agents and models can reason over. Aesthetic identity, personality resonance, use context, emotional tone - all machine-readable, all grounded.
On the user side: we infer psychographic identity from behavioral signals as it forms, so the system works from the first session.
The result is a decision layer that predicts what each person will want - across categories, contexts, and interfaces. Agent, search surface, feed, or API.