VISION
Evidence in the age of AI.
When AI becomes the front door to information, its answers aren't guaranteed to be right.
Verifiable evidence is what can set a trustworthy product apart.
When the medium for information shifts to AI, what happens next? AI-generated information has real reliability gaps — and that is precisely why products backed by verifiable evidence stand out. This page sets out that reasoning, and the role we play in it.
01
The limits of today's AI — and what comes next
Generative AI has spread explosively, and the entry point to information is moving quickly from search to AI. Yet even now, AI's answers still blend a probabilistic mix of the web's good and bad information; misinformation, hallucinations, and claims with uncertain sourcing degrade the experience. That is the industry's shared problem.
And the problem runs deep. Generative AI can fabricate “fake citations” attributed to real experts; even when faithful to its sources it can mislead by stripping away context; and many users simply cannot tell whether an answer is true.
The conclusion is paradoxical but clear: because AI's information is a mixed bag, products backed by verifiable evidence stand out. The quality of the evidence becomes the dividing line of trust.
02
Why evidence works — three structural reasons
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The reliability gap in AI-generated information 1,2,3
Generative AI fabricates “fake citations” attributed to real experts, and can mislead even when faithful to its sources by stripping away context. Many users cannot tell what is true. That is exactly why information backed by verifiable evidence gains relative trust value.
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Strict quality bars for health information 4
Google classifies health and medicine as “YMYL” (Your Money or Your Life) and evaluates quality strictly through E-E-A-T (Experience, Expertise, Authoritativeness, Trust). A framework that rewards authoritative medical sources is already in motion.
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A shift in how people choose (our reading)
Consumers, too, appear to be shifting from “seems good” to “is it backed by evidence?” This is our own reading of the market, not a finding we can cite.
03
Our role in that era
In an era where the quality of trust is under question, what's needed is a partner who can carry evidence all the way through. We split this into three phases and handle them end to end.
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01 / Discern
Evidence
We discern sound evidence from peer-reviewed literature, public data and third-party evaluation, and build it into our own products. Our kansei-engineering know-how and accumulated research sharpen that eye.
Learn more → -
02 / Deliver
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03 / Generate
AI-driven behavior-change service
AI agents on our execution platform ESPL generate evidence-based behavior. Corporate wellness first, then health insurance societies, municipalities, insurance companies and individuals (B2C).
Learn more →
In an era where the reliability of AI-generated information is under question, we discern sound evidence, turn it into products, and have AI generate behavior that lasts. Where AI is the front door to information, we connect evidence to behavior end to end — that is our blueprint.
And AI itself is shifting from advisor to executor. AI agents can draft plans and reports, but they can't move the real world alone — they need an "execution platform" they can call. We announced ours for health behavior in June 2026, and are recruiting partners for a joint PoC (proof of concept) of AI-agent-operated wellness programs.
We call this way of thinking — generating lasting behavior from sound evidence — IDOM (Incentive Driven Outcome Management).
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One discipline beneath what we offer
We deliver products that put vetted evidence into people's hands, and an AI-driven behavior-change service. The same internal discipline supports them: discerning sound evidence from peer-reviewed literature, public data and third-party evaluation. Evidence is the foundation, not a separate offering.
We do not provide contract clinical trials, and we do not handle health foods or foods with function claims. We focus on applying external evidence to our own products and services.
From vetted evidence to products and behavior.
We apply our evidence discipline to our own products and AI-driven behavior-change service.