Research
Alongside the product, NeoRishi studies three questions: why knowing rarely becomes living, how personal rhythm might add useful context, and how a personalised system can explain itself.
Selected work
Yogic psychology & behaviour change
Book chapter manuscript proposing the Knowing-to-Living Framework, which places Pātañjala Yoga concepts in dialogue with behavioural science. The abstract was selected for consideration in Voices in Indian Knowledge Systems, Volume I.
Responsible & explainable AI
Uses the five-part Nyāya inference to make a recommendation’s reasoning inspectable, and reads the classical fallacy of untimeliness (kālātīta) as a check for evidence that has gone stale. Presented as a poster at IIT Delhi in April 2026.
Personal rhythm & time intelligence
Exploring whether several rhythms together, the solar day, sleep and energy, self-reported tendencies and the traditional calendar, give more useful daily context than any one alone.
Yogic psychology & behaviour change
The framework treats change as a sequence that can stall at any point, and asks which practices, Yogic and behavioural, help at each stage.
Status: Working PaperPersonal rhythm & time intelligence
Exploring personal context across biological, behavioural and traditional rhythms.
Status: ExplorationWhether layering rhythms gives a person more useful context for the day than any single tracker or calendar. Parts of this work already run inside Today as transparent rules.
Responsible & explainable AI
Explanations a person can inspect and question.
Status: PrototypePersonalised systems increasingly shape daily choices, yet most cannot say why they recommend what they do. For guidance about health, time and habits, an unexplained recommendation is hard to trust and harder to correct.
NyAI borrows the structure of Nyāya inference, a classical Indian method of reasoning with stated claim, reason, example, application and conclusion, so each recommendation carries an argument that can be checked. It also asks when evidence is too old to rely on.
Bringing NyAI’s explanation structure into NeoRishi’s guidance, starting with the reasons shown behind each Today item.
Method
Every hypothesis pairs a traditional source with current research, and states the strength of the evidence.
Ideas enter the product as simple, testable rules before any AI is involved.
We start with small groups, report what we find, and change our minds in public.
Collect only what a question needs, with consent, and never for sale.