Candid Protocol

Universal Infrastructure Layer for Trust Objects in AI Commerce

Version 1.0 · January 28, 2026

Table of Contents

Executive Summary

As artificial intelligence transforms commerce through platforms like Google's Universal Commerce Protocol (UCP) and OpenAI's Agentic Commerce, a critical gap has emerged: the absence of a standardized, universal infrastructure for trust signals. The Candid Protocol addresses this fundamental need by establishing an extensible framework for trust objects that can seamlessly integrate with any AI commerce system.

Unlike platform-specific trust signals that create data silos and limit merchant reach, Candid Protocol provides a vendor-neutral, future-proof foundation that evolves with commerce technology. Today's trust objects—star ratings, NPS scores, and social reviews—represent only the beginning. Tomorrow's ecosystem will demand sophisticated signals like product return rates, average sale discounts, fulfillment reliability, and sustainability metrics.

This protocol specification defines how trust objects should be structured, transmitted, verified, and integrated across diverse AI commerce platforms, ensuring that merchants maintain consistent trust signals regardless of how consumers discover and purchase their products.

1. Introduction

1.1 The Emergence of AI Commerce

The commerce landscape is undergoing a fundamental transformation. In 2025, Google introduced the Universal Commerce Protocol (UCP), enabling AI agents to seamlessly interact with merchant systems for product discovery, ordering, and fulfillment. Shortly thereafter, OpenAI launched Agentic Commerce, empowering ChatGPT and other AI systems to act as autonomous shopping assistants.

These platforms represent a paradigm shift from human-driven search and browsing to AI-mediated commerce, where algorithms evaluate, compare, and recommend products on behalf of consumers. However, this shift introduces a critical challenge: how do AI systems evaluate trustworthiness and quality when making recommendations?

1.2 The Trust Signal Problem

Traditional e-commerce relies on trust signals that evolved for human decision-making: star ratings, customer reviews, seller badges, and social proof. While these remain valuable, AI commerce demands more:

1.3 Introducing Candid Protocol

Candid Protocol is an open, extensible framework for structuring, transmitting, and verifying trust objects in AI commerce ecosystems. It serves as a universal infrastructure layer that sits between merchants and AI platforms, ensuring trust signals remain consistent, verifiable, and future-proof regardless of how consumers access products.

2. Core Architecture

2.1 Trust Object Definition

A trust object is a structured data entity that represents a verifiable signal about a merchant, product, or transaction. Each trust object contains:

2.2 Trust Object Schema

The base schema provides a flexible, extensible structure:


{
  "candid_version": "1.0",
  "object_id": "uuid-v4",
  "entity": {
    "type": "merchant|product|transaction",
    "id": "unique-identifier",
    "namespace": "merchant-domain.com"
  },
  "trust_signal": {
    "type": "signal-type-identifier",
    "category": "rating|performance|behavior|verification",
    "value": {},
    "unit": "dimensional-unit",
    "timestamp": "ISO-8601"
  },
  "signature": {
    "algorithm": "RS256|ES256|EdDSA",
    "value": "base64-encoded-signature"
  }
}

2.3 Trust Signal Categories

Candid Protocol defines four primary categories of trust signals:

2.3.1 Rating Signals (Current)

2.3.2 Performance Signals (Emerging)

2.3.3 Behavior Signals (Future)

2.3.4 Verification Signals (Foundation)

3. Integration with AI Commerce Platforms

3.1 Universal Commerce Protocol (UCP) Integration

Google's UCP focuses on standardizing product data, ordering processes, and fulfillment operations. Candid Protocol complements UCP by providing the trust layer that UCP lacks.

3.1.1 Integration Approach

Candid trust objects are referenced within UCP product feeds via a standardized extension:


{
  "product": {
    "id": "product-123",
    "title": "Example Product",
    "price": { ... },
    "ucp_extensions": {
      "candid": {
        "trust_signals_url": "https://merchant.com/.well-known/candid/product-123",
        "inline_signals": [
          {
            "type": "review_rating",
            "value": { "average": 4.7, "count": 1523 }
          }
        ]
      }
    }
  }
}

3.1.2 UCP-Specific Considerations

3.2 Agentic Commerce Integration

OpenAI's Agentic Commerce enables conversational AI systems to act as shopping assistants. Candid Protocol provides the trust data that agents use to evaluate and recommend products.

3.2.1 Integration Approach

Agentic Commerce systems retrieve trust objects through two mechanisms:


GET https://merchant.com/.well-known/candid/product-123
Accept: application/json

Response:
{
  "candid_version": "1.0",
  "trust_signals": [ ... ],
  "aggregate_score": {
    "overall": 0.87,
    "category_scores": {
      "rating": 0.94,
      "performance": 0.82
    }
  }
}

3.2.2 Agent Decision Framework

AI agents use Candid trust signals to:

3.3 Future Platform Integration

Candid Protocol's architecture anticipates future AI commerce platforms by providing:

4. Technical Implementation

4.1 Discovery Mechanisms

AI platforms discover Candid trust objects through standardized endpoints:

4.1.1 Well-Known URI


# Merchant-level trust signals
GET https://merchant.com/.well-known/candid/

# Product-level trust signals
GET https://merchant.com/.well-known/candid/products/{product-id}

Merchants can advertise Candid endpoints via HTTP headers on product pages:


Link: <https://merchant.com/.well-known/candid/product-123>;
      rel="candid-trust-signals"; type="application/json"

4.2 Cryptographic Verification

Trust objects are signed using asymmetric cryptography to ensure authenticity and prevent tampering.

4.2.1 Signature Algorithm

Candid Protocol supports multiple signature algorithms:

4.2.2 Key Management

Merchants publish public keys at a well-known endpoint:


GET https://merchant.com/.well-known/candid/keys.json

Response:
{
  "keys": [
    {
      "kid": "2025-01-primary",
      "kty": "RSA",
      "alg": "RS256",
      "use": "sig",
      "n": "base64-modulus",
      "e": "AQAB"
    }
  ]
}

5. Trust Signal Evolution

5.1 Current Trust Landscape

Today's e-commerce trust signals evolved organically over decades, optimized for human decision-making. Candid Protocol formalizes these signals while establishing a foundation for future evolution.

5.2 Emerging Trust Signals

As AI commerce matures, new trust signals will emerge that are particularly relevant to algorithmic decision-making:

5.2.1 Behavioral Metrics

5.2.2 Operational Excellence

5.2.3 Sustainability and Ethics

5.3 Future-Proofing Mechanism

Candid Protocol accommodates new trust signal types through a namespace system:


{
  "trust_signal": {
    "type": "org.candid.sustainability.carbon_footprint",
    "category": "behavior",
    "value": {
      "total_kg_co2e": 12.5,
      "breakdown": {
        "manufacturing": 8.2,
        "transportation": 3.1,
        "packaging": 1.2
      }
    }
  }
}

6. Governance and Standards

6.1 Open Standard Philosophy

Candid Protocol is designed as an open standard, free from proprietary control or licensing restrictions.

6.2 Versioning and Deprecation

Candid Protocol follows semantic versioning (MAJOR.MINOR.PATCH):

7. Implementation Roadmap

7.1 Phase 1: Foundation (Months 1-3)

Objectives:

7.2 Phase 2: Early Adoption (Months 4-9)

Objectives:

7.3 Phase 3: Ecosystem Growth (Months 10-18)

Objectives:

8. Conclusion

8.1 The Imperative for Universal Trust Standards

AI commerce represents a fundamental transformation in how consumers discover and purchase products. As platforms like Google's UCP and OpenAI's Agentic Commerce proliferate, the absence of standardized trust infrastructure creates significant risks for merchants, AI systems, and consumers alike.

8.2 Key Differentiators

Candid Protocol distinguishes itself through:

8.3 Call to Action

We invite stakeholders across the commerce ecosystem to participate in shaping the future of trust infrastructure:

Together, we can build a trust infrastructure worthy of AI commerce's transformative potential.