From browsing to AI-mediated purchasing
As agents execute routine buying, decision power shifts from shelf placement to structured, machine-readable product intelligence.
RightHOLDINGS GROUP INC.
The trust layer for the age of agentic commerce.
We build consented personal product intelligence for health-aware decisions, with RightShop.ai as the first operating venture in a broader holding company thesis.
- Consent-first personal intelligence
- Health-aware product fit signals
- AI-agent purchasing trust controls
Company Thesis
Why agentic commerce needs a consent-based trust layer
We believe the next durable infrastructure category sits between consumer intent, AI delegation, and accountable product intelligence.
Our long-horizon view: as purchasing decisions migrate to software agents, value concentrates in systems that can verify relevance, safety, and fit with explicit user consent.
Trust infrastructure becomes core market plumbing
Agentic flows require verifiable provenance, policy alignment, and transparent ranking logic to support repeatable outcomes.
Consented personal intelligence is the missing input
Durable personalization starts with explicit permission and user-controlled context, not inferred profiles or opaque behavioral guesswork.
Health-aware purchasing is a compelling first wedge
Health-context decisions are high-frequency and high-consequence, making them the right proving ground for trusted agentic commerce.
First Venture Proof Point
RightShop.ai: personal product intelligence for agentic commerce
RightShop.ai operationalizes the holding company thesis through consented data, explainable scoring, and real-time fit decisions at the moment of purchase.
Consented health profile
Users define a consented profile of sensitivities, preferences, and health priorities. The profile is portable, auditable, and permission-based by design.
RightScore engine
RightScore translates profile and product data into an explainable fit score with transparent factor weighting, enabling confidence instead of black-box recommendations.
Point-of-purchase fit evaluation
At decision time, the system evaluates product fit against the user profile and flags potential mismatches before a transaction is completed.
Trust layer for AI agents
RightShop.ai provides a callable trust layer that agentic systems can use to align recommendations and purchases with user-consented health constraints.
Validation through operating principles
A disciplined framework for building durable trust in AI-mediated commerce.
Consent-first design
User permission is foundational to data use, model behavior, and platform governance.
Health-aware intelligence
Recommendations are informed by personal health context rather than generic purchase signals.
Long-horizon company building
Execution favors durable infrastructure, measured deployment, and compounding strategic value.
Trust for AI-mediated purchasing
The trust layer is designed for accountable decisions as autonomous agents influence commerce.
Leadership
Human credibility behind the thesis.
Our leadership discipline centers on long-horizon strategy, product clarity, and governance built for durable trust in health-aware agentic commerce.
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Michelle Martin
Co-Founder & Chief Executive Officer
Leads business strategy with a focus on strategic partnerships, measurable governance, and durable value creation.
Shreya Vohora
Co-Founder, President & Chief Product Officer
Co-leads business strategy and heads product direction and the RightScore roadmap, ensuring consent-first architecture.
Investor FAQ
Practical answers before you reach out
What is RightHolding Group building?
We are building a holding company focused on consented personal product intelligence for health-aware, agentic commerce. Our thesis is to become a trust layer that helps autonomous buying systems make safer, better-aligned product choices.
Why is RightShop.ai the first project in the portfolio?
RightShop.ai is the initial proof point because it tests the core thesis in a live market: using a consented health lens and the RightScore engine to improve product decisions in commerce workflows.
How are investor information requests handled?
Requests are reviewed through a consent-based process. Qualified investor inquiries receive follow-up materials aligned to the request, and broader strategy discussions are scheduled directly with the company team.
What does consented follow-up mean in practice?
It means communication occurs only after an explicit request, for the stated purpose, with clear boundaries on what is shared and when. The model prioritizes trust, relevance, and respectful data handling.
Who is this site intended for?
This site is for investors, strategic partners, and informed stakeholders evaluating the long-term holding company thesis and the role of RightShop.ai as its first operating venture.
If you want the full thesis deck or a direct conversation, please request investor information.