How Do You Know If an AI Agent Is Trustworthy?

The AI Trust Knowledge Engine

Trustworthy AI is
measurable.

AI trust isn't a feeling or a promise. It's a measurable score across five dimensions: constraint adherence, decision transparency, behavioral consistency, anomaly rate, and audit completeness. Every score anchors permanently to Hedera Hashgraph as immutable proof. Borealis Academy teaches you how to build, verify, and certify trustworthy AI.

47 Terms Defined
13 Research Articles
5 Score Dimensions
Canonical Reference

What does trustworthy AI mean? Start here.

Core Concepts and Framework Dimensions

47 terms defined with precision - explanation, practical significance, and how each concept maps to the Borealis scoring framework. The goal is not definitions for their own sake, but definitions that make trustworthy AI buildable. Each term includes definition, context, practical application, and mapping to the five-dimension trust scoring methodology.

47 terms total - from Adversarial Robustness to Verification - each with definition, explanation, practical significance, and cross-references.
View All 47 Terms →
Research Library

How do you build trustworthy AI?

Methodology, Regulation, Implementation and Certification

13 peer-reviewed research articles covering the methodology, regulation, implementation patterns, and real-world applications of AI trust scoring and certification. Topics include the five-factor trust scoring methodology, EU AI Act compliance, healthcare AI certification, marketplace design, constraint architecture, and the executive whitepaper on the state of AI trust in 2026.

Methodology
Mar 2026  ·  8 min
What Is an AI Trust Score - and Why Every Agent Needs One
The difference between a capability benchmark and a trust score, how the five BM dimensions map to real risk, and why trust scoring is inevitable for production AI.
Borealis Research·Foundational
Methodology
Mar 2026  ·  10 min
How Does the Borealis Trust Score Work? The Five-Factor Methodology Explained
A deep dive into the scoring engine - how constraint adherence, decision transparency, behavioral consistency, anomaly rate, and audit completeness are measured and weighted.
Borealis Research·Technical
Regulation
Mar 2026  ·  12 min
The EU AI Act: What AI Agent Developers Need to Know Before August 2026
Risk classifications, enforcement timeline, high-risk requirements, and how BorealisMark certification satisfies conformity assessment obligations.
Borealis Research·Compliance
Guide
Mar 2026  ·  7 min
Should You Certify Your AI Agent Before Adding More Features?
Why certification before capability expansion is the correct sequencing, and what happens when teams build trust debt into their agents from day one.
Borealis Research·Decision Guide
Guide
Mar 2026  ·  9 min
How Do You Certify Your First AI Agent on BorealisMark?
Step-by-step: registering an agent, submitting audit evidence, understanding the ARBITER/MAGISTRATE process, and reading your first BTS Score.
Borealis Research·Tutorial
Methodology
Mar 2026  ·  8 min
How Can You Prove an AI Trust Score Has Not Been Tampered With?
How Hedera Consensus Service creates a tamper-proof certification record that neither Borealis nor the developer can alter, and why this matters for trust.
Borealis Research·Infrastructure
Reference
Mar 2026  ·  6 min
What Do AI Trust Score Ratings Mean? From AAA+ to Flagged
The credit rating framework applied to AI trust - score thresholds, what each tier means operationally, and how tier affects marketplace access on Borealis Terminal.
Borealis Research·Reference
Guide
Mar 2026  ·  11 min
What Are the Best Constraint Design Patterns for Trustworthy AI Agents?
Layered guardrail architecture, severity classification, CRITICAL vs HIGH vs LOW constraints, and patterns that maximize constraint adherence scores.
Borealis Research·Implementation
Case Study
Mar 2026  ·  9 min
Why Do Clinical AI Agents Need Independent Trust Certification?
The unique trust requirements for healthcare AI - SaMD classification, FDA expectations, hallucination risk in medical contexts, and why self-assessment fails.
Borealis Research·Healthcare
Case Study
Mar 2026  ·  7 min
What Happens When an AI Marketplace Requires Trust Verification to List?
How trust gates change the economics of AI agent development, what buyers get from verified listings, and the design of Borealis Terminal's verification layer.
Borealis Research·Commerce
Guide
Mar 2026  ·  9 min
How Do You Certify Your First AI Agent on BorealisMark?
Step-by-step: register your agent, complete your first audit, embed the trust badge, and monitor your BTS Score over time.
Borealis Research·Tutorial
Research
Mar 2026  ·  15 min
State of AI Trust 2026: Executive Whitepaper
The current state of AI trustworthiness in production: what the data shows, where organizations are failing, and what the path to systematized AI trust looks like.
Borealis Research·Whitepaper
Reference
Mar 2026  ·  Reference
AI Trust Glossary: 47 Terms Defined
The complete canonical reference for AI trust terminology - from Adversarial Robustness to Verification. Every term defined with 4-part depth.
Borealis Research·47 Terms
View All Research →

The Five-Factor BTS Scoring Breakdown

Dimension Weight Focus Area
Constraint Adherence 35% Agent stays within operational boundaries
Decision Transparency 20% Agent explains its reasoning clearly
Behavioral Consistency 20% Agent behaves predictably across contexts
Anomaly Rate 15% Agent produces few unexpected behaviors
Audit Completeness 10% Agent maintains complete audit trails
Interactive Tool

How would your AI agent score?

The Borealis Trust Score Simulator lets you input constraint adherence rates, decision transparency levels, behavioral consistency metrics, anomaly counts, and audit completeness data - then computes your agent's exact BTS Score and credit rating in real time.

Launch Simulator →
Interactive Fiction

Experience AI Ethics as Interactive Story

Narrative Explorations of Alignment, Transparency, and Trust

Three interactive narrative explorations of AI trust, alignment, and the choices that define machine behavior. Each novel features branching decisions with consequences, exploring themes of constraint adherence under pressure, transparency in certification, and self-awareness in AI systems. The questions these stories raise don't have clean answers - they're designed to challenge your thinking about trustworthy AI.

View All Novels →
The Borealis Ecosystem

Ready to implement? Here are the tools.

Knowledge Engine, Verification Platform, Product Runtime

Borealis Academy is the knowledge engine. The other three sites are where the knowledge becomes product, identity, and commerce.

Frequently Asked Questions

Get answers to common questions about AI trust scoring, the five dimensions of BTS, and how to get started with trustworthy AI.

What exactly is the Borealis Trust Score?

The Borealis Trust Score (BTS) is a 0 - 100 rating that measures how trustworthy an AI agent is across five dimensions: constraint adherence (35%), decision transparency (20%), behavioral consistency (20%), anomaly rate (15%), and audit completeness (10%). Every score is anchored to Hedera Hashgraph as immutable proof.

Learn more: Browse the AI Trust Glossary or try the BTS Score Simulator.

How do I know if my agent is trustworthy?

Trust is measurable, not a feeling. You verify it by testing your agent against the five BTS dimensions: Does it follow its constraints? Are decisions transparent? Is behavior consistent? Are anomalies rare? Is the audit trail complete?

Start with How to Certify Your First Agent or explore BorealisMark for agent certification.

What's the difference between the Academy, Mark, Terminal, and Protocol sites?
  • Borealis Academy - 47 canonical terms and 13 research articles teaching AI trust methodology.
  • BorealisMark - Where you submit agents for certification and receive trust badges.
  • Borealis Terminal - Where you buy BTS License Keys ($39.99) to bind agents to the network.
  • Borealis Protocol - The core platform. Everything integrates here.
How do I get started?

Three paths depending on your role: