AI Lab
Meet Rushi
Rushi is an experimental human-centered AI rules engine that attempts to embody uncompromising ethics, morals, and values to ensure consistent results in high-stakes environments and situations.
2026 Copyright IDRUSHI LLC
Background
Most AI engines today are developed as language models. Some include analyzing patterns in words, visuals, sounds, numbers, and material properties.
Several languages (including English) are known to be imprecise; hence, interpretation is highly contextual.
Linguistic, cultural, and contextual differences create nuanced inconsistencies in the way AI engines interpret data.
Each LLM AI engine has developed its own framework and guiding principles for ethics, morals, and values that are applied when they respond, make decisions, or perform any task.
These differences and limitations cause small variations in the way AI engines respond to prompts, make decisions, and perform tasks.
RESPONSE / ACTION
Imprecise language ​
Cultural differences ​​
Difference in Training​​​​​
Accurate \ Optimal
PROMPT
Problem statement
Nuanced differences in how AI engines interpret ​data, respond and perform task can be overlooked in low stake environment because they provide benefits that outweigh the limitations of accuracy or consistency.
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In high stake environments where health, wealth, safety and security of humans are at risk ( Financial services, law enforcement, Judicial systems and defense and Regulatory ) such nuanced differences might yield inconsistent decisions, actions and can be manipulated to promote certain outcomes or have inherent bias. ​​​
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Use of AI in high stake environment is rapidly increasing but such AI decision are largely reliant of reason interpretation of the law and the regulation oftentimes t laws and regulations that rely interpretation of words have not caught up to unique situations ​
Progress
Rushi is in a the early stages of development. ​​
The most recent research done was using an experimental list of over 200 rules. The objective of the research was to ​:
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1. Prove with evidence that Current LLMs and products are inconsistent in the way they think during high stake situations.
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2. When stakes increase beyond a certain limit LLMs demonstrated a very high degree of instability, bias thereby exposing themselves for manipulation.
3. Hard uncompromising rules configured in the larger interest of humanity can deliver consistent outcomes free from bias or risk of manipulation..​​
We are here
Rushi is a viable product
