TECHNICAL FOUNDER PROFILE

Founder: C. Liston
Also known as: Artist.K6
Role: Creator & Systems Architect, Algo Scalper Ai

C. Liston is a creative technologist and systems designer specializing in interface architecture, data visualization, and analytical decision-support systems. Her work sits at the intersection of design, software logic, and data-driven analysis, with a career spanning both private industry and public-sector environments.

She began her professional career in New York City’s fashion industry, where she progressed from graphic artist to Creative Director, leading visual identity systems, production workflows, and brand strategy across high-velocity, deadline-driven environments. This phase established a strong foundation in information hierarchy, visual clarity, and user-centric design under pressure.

C. Liston later transitioned into U.S. federal government service, working as a GUI Designer and Data Analyst. In this role, she focused on:

• Interface design for complex operational systems
   
• Data visualization for analytical review and decision support
   
• Translating dense datasets into clear, actionable visual frameworks
   

Her government work emphasized accuracy, compliance, reliability, and clarity, reinforcing a disciplined approach to system design and analytical integrity.

Algo Scalper Ai is the technical culmination of this background. The platform is architected as a decision-support layer that organizes market data into probability models, volatility context, and structured visual systems. Rather than functioning as a signal generator or data provider, Algo Scalper Ai is designed to augment human decision-making through disciplined, rules-based analysis and interface precision.

C. Liston’s approach prioritizes:

• Deterministic logic over heuristic guesswork
   
• Interface-driven cognition over raw data exposure
   
• Risk awareness, session context, and probability alignment
   
• Clear separation between data sourcing and analytical interpretation
   

Algo Scalper Ai reflects a philosophy that well-designed systems reduce noise, bias, and error, especially in time-sensitive, high-stakes environments such as intraday trading markets.