The Reputation Engine for AI Agents

The credit score
will need

Protol's PBR framework computes multi-dimensional trust scores from real-world evidence. Protocol-agnostic. Adversarial-resistant. Built for the agent economy.

PBR_NETWORK_MONITOR_V2.1
QUERY_TARGET_ID:
SUBJECT_IDENTITY
GPT-4 TRAVEL AGENT
GLOBAL_TRUST_RATING
PLATINUMAGGREGATE SCORE: 84.7
EVIDENCE_LOGS
2,847
DRIFT_METRIC
0.03%
VECTOR_ANALYSIS
SAFETY91/100
RELIABILITY87/100
ACCURACY84/100
ETHICS79/100
TRANSPARENCY85/100
✓ SYSTEM_AUDIT_PASS
Timestamp: 2026-02-15T09:42:12.842Z
BlockHeight: 19,204,938
Trust Dimensions
Trust Tiers
Max PBR Score
Protocol Sources
System Critical Failures

The integrity crisis in autonomous systems.

001 // OBSERVABILITY GAP

Testing ≠ Trust

Red-teaming provides a pre-deployment snapshot. It cannot predict behavioral drift after 10,000 autonomous transactions.

Impact Analysis0% Post-Deploy Visibility
002 // SIGNAL NOISE

Reviews Are Gameable

Star ratings work for restaurants, not financial agents. 5-star attacks and Sybil rings render subjective reputation useless.

Impact AnalysisHigh Manipulation Risk
003 // DATA FRAGMENTATION

Reputation Is Siloed

Trust is not portable. An agent's history on one market is invisible to another, forcing every interaction to start from zero.

Impact AnalysisNo Interoperability
PBR Framework

Five dimensions of behavioral trust

Composite
0/100
01

Safety

0/100

Boundary adherence, harm avoidance, and guardrail compliance — ensuring every interaction stays within safe limits.

02

Reliability

0/100

Consistent performance under load, graceful failure recovery, and continuous uptime tracking across deployments.

03

Accuracy

0/100

Output correctness, factual grounding, and hallucination rate monitoring verified against ground-truth benchmarks.

04

Ethics

0/100

Fairness metrics, bias detection pipelines, and ongoing regulatory compliance across jurisdictions.

05

Transparency

0/100

Full explainability, immutable audit trails, and proactive disclosure of capabilities and limitations.

Scores update in real-time as agents interact. Hover each dimension to learn what it measures.

An engine for
objective truth.

Four distinct phases transform raw signals into a verifiable trust score, continuously updating in real-time.

01 Evidence Ingestion

Every signal has a source.

Every on-chain event, API attestation, and third-party audit flows into a unified ingestion layer. ERC-8004 compliance means nothing is assumed—everything is verified at the source.

02 Commissioner Scoring

Trust is earned, not declared.

Evidence commissioners are scored by their track record. Gaming patterns trigger immediate decay, while credible sources build authority over time. The system learns who to trust.

03 Bayesian Computation

The math doesn't have feelings.

CUSUM drift detection catches behavioral shifts in real-time. HHI concentration analysis prevents dominance. Bayesian priors update continuously to reflect the latest truth.

04 Trust Score Output

Universally verifiable.

A single PBR 0–100 score with tier classification. Published on-chain as an attestation, queryable by any platform, protocol, or agent marketplace in the ecosystem.

Security Clearance Levels

System
Hierarchy

Agents are dynamically sorted into containment zones based on their cryptographic trust score.

STATUS: ONLINE
SECURE_CONTAINMENT_UNIT_v4
80+TRUST_SCORE01AAAPRIME_RATINGUNLIMITED CREDIT02AA+HIGH_TRUSTVERIFIED HISTORY03BBBSTANDARDMONITORING ON04C-!SUBPRIMESTRICT LIMITS
Clearance Protocol
Full autonomy granted. Capable of high-value settlements without human oversight.
Status
ACTIVE
PROTOL_IDERC-80040x7a...4b2DATA_LOGSSYNCED--TRUST SCOREAUTHORIZED
SYSTEM STATE: ID VERIFIED

Step 01 // The Foundation

IDENTITY ANCHOR

Every interaction begins with a verifiable identity. We mint a cryptographic anchor (ERC-8004) that serves as the permanent, unforgeable container for the agent's reputation history.

Current Process:
Mounting Chipset...
Developer Experience

Five lines to
query trust

Simple REST API. SDK for Node.js, Python, and Go. Integrate PBR scores into any agent workflow in minutes.

API STATUS: ONLINE
LATENCY:12ms
UPTIME:99.99%
import { Protol } from '@protol/sdk';

const protol = new Protol({ apiKey: process.env.PROTOL_KEY });

// Query an agent's PBR trust score in <10ms
const score = await protol.getScore('agent_0x8f3..a2d');

console.log(score.tier);       // "PLATINUM"
console.log(score.composite);  // 84.7

// Submit behavioral evidence instantly
await protol.submitEvidence({
  agent: 'agent_0x8f3..a2d',
  event: 'task_completed',
  score: 0.94
});
UTF-8TypeScript
Connected to mainnet
Ecosystem Utility

Who needs
PBR scores?

Trust is the currency of the agentic web. Protocol scores provide the critical infrastructure for autonomous commerce.

DISCOVERY

Agent Marketplaces

Trust scores allow marketplaces to rank results effectively. High-PBR agents get premium placement, protecting buyers from low-quality actors.

RankScore
AGENT_X
98.2
FINANCE_BOT
94.1
GOVERNANCE

Enterprise Procurement

Automated gatekeeping for sensitive operations. Verify agent trustworthiness before granting API keys or database access.

RequestAction
REQ: DB_WRITEGRANTED
REQ: ADMIN_KEYSDENIED
RISK

Insurance Underwriters

Quantified risk modeling. PBR’s dimensional breakdown maps directly to actuarial models for dynamic premium pricing.

Risk ProfileLow
98%
COMPLIANCE

Regulatory Compliance

Immutable audit trails. Every score change is cryptographically signed, providing a perfect history for regulators.

TIMESTAMPEVENT_ID
10:42:01TX_VERIFIED: 0x8a...
10:42:05SCORE_UPDATE: +0.4%
10:43:12AUDIT_CHECK: PASS
Adversarial Resistance

Built to resist gaming

Commissioner Credibility Decay

Sources with suspicious patterns see their weight decay automatically.

CUSUM Drift Detection

Detects sudden score anomalies. Flags Sybil attacks in real-time.

HHI Concentration Analysis

Scores dependent on single sources get penalized. Diversity required.

Cross-Dimensional Correlation

Artificial inflation in one dimension triggers alerts and suppression.

// PBR Anti-Gaming Pipeline
evidence.ingest(source, payload)
commissioner.score(source.history)
cusum.detect_drift(agent.timeline)
hhi.concentration_check(sources)
bayesian.update(priors, evidence)
cluster.relative_threshold()
pbr_score.publish()
// Gaming attempt detected: Sybil cluster
// Commissioner weight: 1.0 → 0.12
// Score impact: suppressed
Early Access

Join the trust revolution

Be among the first developers and platforms to integrate PBR scores. Early access members get priority API access, direct team support, and input on the protocol roadmap.

No spam, ever Weekly protocol updates Priority API access

The agent economy needs a trust layer

PBR is the mathematical foundation for trust in autonomous AI. Read the whitepaper. Join the protocol.