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Global Clean Energy Inc. Highlights Flamelit's Proven AI Delivery Across Public Sector, Healthcare, Security, and Data Infrastructure

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Global Clean Energy (OTCID: GCEI) highlighted Flamelit, its domain-focused AI delivery platform, and described production deployments across healthcare, public health, security, and disaster-response environments.

Flamelit emphasizes rapid prototype-to-production paths, measurable outcomes, and iterative improvement through live customer use with partners named in the announcement.

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HOUSTON, April 29, 2026 /PRNewswire/ -- Global Clean Energy, Inc. (OTCID: GCEI) today highlighted the operating track record of Flamelit, its execution-focused AI platform that is already delivering production systems for customers across healthcare, public health, security, and disaster-related environments.
Flamelit was built on a practical premise: AI creates value when it is deployed inside real-world domains with urgent needs, measurable outcomes, and a clear path from prototype to production. Rather than operating as a general-purpose AI lab, Flamelit focuses on domain-specific applications that can be implemented, licensed, and improved through live customer use. 

"Flamelit is about execution," said Dr. Earl Azimov, CEO. "The company's strength is not just building AI models, but delivering systems that operate in environments where reliability, speed, and measurable outcomes matter."

Flamelit's body of work already spans multiple mission-critical sectors:

  • Healthcare and clinical AI: Flamelit has delivered solutions for healthcare providers and research organizations, including work with Parkland Center for Clinical Innovation, such as early sepsis detection models using minimal patient intake data, pediatric asthma risk forecasting, and public health analytics integrating environmental and clinical signals. 
  • Security and biometrics: Within the U.S. Department of Homeland Security ecosystem, including U.S. Citizenship and Immigration Services, Flamelit has supported AI classifiers for biometric capture quality, predictive models to improve system responsiveness, and embedded analytics for operational monitoring and decision support. 
  • Public health and data platforms: For agencies including the Centers for Disease Control and Prevention, Flamelit has helped modernize large-scale health data repositories, build real-time dashboards tracking disease trends and outcomes, and deliver advanced analytics to support faster, evidence-based decisions. 
  • Natural disaster and emergency response: Flamelit serves as a core delivery partner to AI for Natural Disasters, helping develop a multimodal AI platform designed to provide predictive intelligence across disaster scenarios. 

This work reflects Flamelit's domain-first operating model, which emphasizes faster deployment, shorter paths from prototype to production, measurable return on investment, and continuous improvement through real-world feedback.
Global Clean Energy believes this proven delivery history positions Flamelit as a differentiated player in applied artificial intelligence, with a foundation already established through customer work rather than speculative development. 

About Global Clean Energy, Inc. (GCEI)
Global Clean Energy drives the transition to sustainable infrastructure through innovative AI, energy solutions, and resilience technologies.

Forward-Looking Statements
Statements in this release may be regarded, in certain instances, as "forward-looking statements" pursuant to certain sections of the Securities Act 1933 and the Securities Exchange Act 1934, respectively. "Forward-looking statements" are based on expectations, estimates and projections at the time the statements are made, and involve risks and uncertainties, which could cause actual results or events to differ materially from those currently anticipated, including, but not limited to delays, difficulties, changed strategies, or unanticipated factors or circumstances affecting Global Clean Energy Inc. and its business. There can be no assurance that such forward-looking statements will ever prove to be accurate, and readers should not place undue reliance on any such forward-looking statements contained herein. Global Clean Energy Inc. will not republish revised forward-looking statements to reflect events or circumstances after the date hereof to reflect the occurrence of unanticipated events.

https://globalcleanenergy.net         
https://globalcleanenergy.net/blog
https://www.flamelit.tech

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SOURCE Global Clean Energy Inc.

FAQ

What deployments does Flamelit (GCEI) claim across healthcare and clinical settings?

Flamelit has delivered clinical AI solutions including early sepsis detection and pediatric asthma risk forecasting. According to Global Clean Energy, these projects used minimal intake data and integrated environmental and clinical signals for actionable insights.

Which U.S. agencies has Flamelit worked with, according to GCEI?

Flamelit reports work within the Department of Homeland Security ecosystem and with U.S. Citizenship and Immigration Services. According to Global Clean Energy, the work included biometric capture quality classifiers and embedded operational analytics.

How does Flamelit support public health data platforms, per GCEI's announcement?

Flamelit helped modernize large health data repositories and build real-time dashboards tracking disease trends and outcomes. According to Global Clean Energy, these efforts aimed to speed evidence-based decision making for agencies like CDC.

What role does Flamelit play in natural disaster and emergency response solutions?

Flamelit serves as a core delivery partner to AI for Natural Disasters, developing a multimodal predictive intelligence platform. According to Global Clean Energy, the platform targets predictive insights across multiple disaster scenarios for responders.

What is Flamelit's operating model as described by Global Clean Energy (GCEI)?

Flamelit follows a domain-first model focused on deploying production systems with measurable ROI and fast prototype-to-production paths. According to Global Clean Energy, the approach prioritizes reliability, speed, and live-customer improvement over general-purpose AI research.