TRUST.AI
Building a Research-Driven Trust Layer for Digital Communication
TRUST.AI is an emerging research and product initiative focused on helping individuals and organizations evaluate digital interactions before responding, clicking, sharing information, or making financial decisions.
Why Digital Trust Matters
Digital communication has become easier than ever.
Trust has not.
Every day people communicate through email, SMS, WhatsApp, websites, phone calls, QR codes and AI assistants.
Yet there is still no universal way to determine whether a digital interaction should be trusted before taking action.
What TRUST.AI is exploring.
Four open questions guide the current research and product work.
Help validate the problem.
These short, anonymous surveys inform the research. Your responses directly shape what TRUST.AI investigates and prioritizes.
Anonymous submission. We store a privacy-preserving salted hash of your IP and browser for provenance only.
Tap a channel to submit your vote.
Anonymous submission. We store a privacy-preserving salted hash of your IP and browser for provenance only.
Anonymous submission. We store a privacy-preserving salted hash of your IP and browser for provenance only.
From research concept to working MVP.
The current TRUST.AI MVP demonstrates an early trust-assessment workflow for digital content, websites, senders, and online interactions. It is intended to support technical experimentation, user validation, and responsible product development.
Note: The MVP is not a substitute for professional cybersecurity, legal, or financial advice.
A unified trust-assessment framework.
The objective is not to replace human judgment. TRUST.AI is designed to provide decision support — presenting risk indicators, explanations, and verification context before users engage.
Responsible development from the beginning.
Every design decision is measured against the same set of commitments.
Collect only the information necessary for risk assessment.
Show users why an interaction may be considered trustworthy, uncertain, or risky.
The user remains responsible for the final decision.
Clearly distinguish verified identities, inferred signals, and unverified claims.
Evaluate false positives, false negatives, and uneven model behavior.
Protect sensitive information and minimize unnecessary data exposure.
- Enterprise software engineer
- Independent researcher
- IEEE Senior Member
- Peer reviewer
- Technology entrepreneur
An initiative led by Prashanth Chevva.
TRUST.AI was initiated by Prashanth Chevva, an enterprise software engineer, independent researcher, IEEE Senior Member, peer reviewer, and technology entrepreneur. His professional work spans enterprise healthcare systems, distributed software, privacy-first analytics, artificial intelligence, and logistics technology.
TRUST.AI represents the next stage of his work — applying research, enterprise engineering experience, and responsible AI principles to the challenge of digital trust and fraud prevention.
What comes next.
A multi-phase program. The initiative is currently in early public validation.
User interviews, threat analysis, responsible AI requirements, and problem validation.
Message analysis, website assessment, sender verification, and explainable risk scoring.
Collaborations with recruiters, small businesses, professional service firms, researchers, and digital-safety organizations.
Browser tools, business verification, APIs, and cross-channel trust intelligence.
Security testing, model evaluation, privacy review, and external research collaboration.
Seeking researchers, pilot partners, and early users.
TRUST.AI is currently seeking feedback and collaboration from researchers, cybersecurity professionals, ethical AI specialists, businesses, universities, and individuals affected by digital fraud.
Frequently asked questions
Help shape the future of digital trust.
TRUST.AI is still being developed. Join as an early user, researcher, or organization and help validate what a trust layer for digital communication should look like.