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For 70 years, trust has been studied in psychology but never given a measurable unit in business. Leaders measure revenue, profit, and engagement — but not trust, the very force driving all three. TRUST OR™ introduces the first patent-pending Trust Score equation.

Work is being rewritten by AI — but trust hasn’t caught up.
Executives are investing billions in sales tech, HR tech, and leadership training, yet none of these tools measure or build the most critical currency in human performance: trust.
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The timing is unique:
Market pressure: Hybrid work, distributed teams, and AI-driven interactions are exposing trust gaps faster than ever.
Tech readiness: Advances in AI, NLP, and behavioral analytics now make trust measurable in real time.
Budget shift: Enterprises are already spending $300B+ annually on training and enablement — they’re looking for ROI and accountability, not just soft-skill workshops.
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TRUST OR™ is seizing this window to define a new category — TrustTech — turning trust into a metric leaders can measure, train, and invest in.

The global corporate training and enablement market is worth over $300B, with leadership, communication, and sales enablement alone representing a $20–30B opportunity.
Trust cuts across every function — sales, leadership, HR, customer success, and compliance. By focusing first on enterprise sales and leadership development, TRUST OR™ is entering a €10–15B serviceable market in Europe and North America.
Our mission is bigger: to define and own a new category — TrustTech — where trust becomes a measurable, trainable, and investable asset.

We’ve already filed a U.S. non-provisional utility patent covering the full TRUST OR™ system, including its engines (T, L, R, D), scoring logic, and CRM integration.
A trademark has also been filed in the EU to protect the brand across multiple classes.
To reinforce this moat, I am also preparing a direct filing with the European Patent Office (EPO) to secure patent protection across Europe.
This dual-track strategy (USPTO + EPO) ensures that TRUST OR™ is not only protected in the U.S. but also in the world’s second largest enterprise market.

TRUST OR™ is built with privacy and compliance by design.
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GDPR-first architecture: All data processing is aligned with EU GDPR and international privacy standards. Personally identifiable information (PII) is minimized, anonymized, or aggregated before analysis.
On-premise & cloud flexibility: Sensitive client data can be processed in secure enterprise environments or encrypted cloud instances, depending on customer requirements.
Transparency & consent: Every engagement includes clear opt-in, data usage transparency, and the ability to delete or export records on request.
Security protocols: End-to-end encryption (in transit and at rest), strict access controls, and regular penetration testing ensure enterprise-grade security.

TRUST OR™ does not “spy” or store private conversations. Instead, it analyzes behavioral signals (tone, rhythm, language congruence) within approved professional settings — producing trust scores without exposing personal content.

TRUST OR™ was designed to work across three input levels:
Full-signal mode (video + audio + text): Delivers the most precise scoring by analyzing multi-channel cues (tone, micro-expressions, rhythm).
Audio + text mode: Still highly accurate — captures language, tone, pacing, and conversational rhythm.
Text-only mode (transcripts, chat, CRM notes): Accuracy is lower, but TRUST OR™ can still detect language congruence, repetition, and distortion signals, which are powerful trust indicators.

Even without video or audio, TRUST OR™ maintains signal reliability because:
Trust doesn’t depend on one channel. Congruence (T + L + R / D) can be measured in words and patterns alone.
Many enterprise workflows (CRM, email, chat) are text-based, so text scoring ensures broad adoption.
Our Fluency Engine continuously improves accuracy by learning from each interaction and enriching the libraries.

Accuracy hierarchy:
Video + audio + text → gold standard (highest trust resolution).
Audio + text → ~80–85% of full accuracy.
Text-only → ~60–70%, still valuable for CRM integration and large-scale analysis.

Paid pilot programs with leading companies.Phase 2:
SaaS subscriptions for teams and enterprises.Phase 3:
Global scaling via partnerships and integrations.Phase 4:
Establishing TRUST OR™ as the global standard for measuring trust in business.*

Brand, IP, and thought-leadership ecosystem established.
Engagement with incubators and innovation hubs underway.
Early inbound interest from enterprise leaders exploring pilots.

For two decades, Weiwei Chen worked at the frontline of enterprise sales. She saw how even the strongest strategies could fail when trust fractured — and how success came when trust aligned. That experience inspired her to create TRUST OR™, the first system designed to make trust measurable and usable.

Every startup carries risk. For TRUST OR™, the main risks are execution and adoption speed. The concept of making trust measurable is new, which means we must educate the market as well as build the product. In the short term, early pilots may run on semi-manual processes before full SaaS automation is ready. In the long term, our success depends on scaling data collection and integrations fast enough to establish TRUST OR™ as the standard. The advantage is that trust has been invisible for decades — the demand is clear, the problem is universal, and the first mover has a unique opportunity to define the category.