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AIPolicyCompare
↳ THE METHOD

An engine
reads every
AI clause.
Then we
cite it.

AIPolicyCompare is a public record of how 527 AI platforms treat user content, prompts, outputs, and training rights. Every finding ships with the verbatim policy quote that supports it.

01 · AUTOMATED PIPELINE

Every clause is scored by an AI reasoning engine.

Policy documents are fetched automatically three times per week and split into clauses by paragraph and section. Each clause is evaluated against five specific questions about IP ownership and privacy risk. Ratings are computed deterministically from those per-clause evaluations.

02 · VERBATIM ONLY

No paraphrase. Every finding ships with the source quote.

Every surface verdict on a platform record is paired with the verbatim language from the source policy, the exact section reference, and a link back to the original document.

03 · CONTINUOUS UPDATES

When a policy changes, the rating re-computes automatically.

When a source document changes, the affected clauses are re-evaluated automatically and the rating recomputed. Changes appear in the Updates feed within 24 hours of detection.

↳ THE SIX SURFACES WE TRACK

Every record · every surface · every tier.

P
PROMPT OWNERSHIP
Who owns the text, images, or files you submit as input.

We look for explicit ownership-retention language and any rights the user grants to the platform via license or assignment.

O
OUTPUT OWNERSHIP
Who owns the AI-generated content you receive.

We capture the platform's position on output rights, including any conditions on output ownership (compliance with usage policies, attribution, etc.).

T
MODEL TRAINING
Whether your submissions train future models.

We capture the default behavior (on or off), the visibility of the opt-out, and any tier-by-tier carve-outs.

C
COMMERCIAL USE
Whether you can use outputs for business, monetization, or resale.

We capture restrictions, revenue thresholds, and any tier-gated commercial provisions.

D
DATA RETENTION
How long the platform stores your prompts, outputs, and account data.

We capture the stated retention window, exceptions (T&S, legal hold, feedback), and any zero-retention configurations.

$
TIER DIFFERENCES
How free, pro, team, enterprise, and API tiers diverge.

We capture which surfaces materially change between tiers — especially training defaults, retention windows, and commercial use protections.

↳ THE FIVE QUESTIONS

The engine answers five questions for every clause.

  1. 1

    Does this give the platform rights to user inputs beyond service delivery?

  2. 2

    Does this affect who owns the outputs?

  3. 3

    Does this permit training on user content?

  4. 4

    Does this restrict commercial use of outputs?

  5. 5

    How long is user data retained?

↳ THE RATING RULES

Deterministic. No judgment calls.

The overall rating is the most severe single-clause verdict. The same clauses always produce the same rating — the decision table below is the entire logic.

LOW

No clause meets the MED or HIGH criteria.

MED

Any single clause grants a broad (non-sublicensable) license to inputs, OR enables training with an opt-out, OR restricts commercial use of outputs.

HIGH

Any single clause grants sublicensable rights to inputs, OR claims output ownership, OR permits training with no opt-out.

CROSS-DOCUMENT CONTRADICTION SCAN

Our pipeline continuously performs a pass looking for conflicting statements across different legal documents published by the same platform (e.g., between their Terms of Service and Privacy Policy). When directly contradictory answers are found to the same question, this is flagged as a Conflict.

Because conflicts represent severe legal and compliance exposure for corporate reviews, platforms with active contradictions are automatically given a rating of MED (or HIGH depending on the clause severity) to ensure reviewer visibility, accompanied by a special warning banner highlighting the specific conflicting excerpts.

↳ THE WORKFLOW

From source document to public record.

  1. 01

    Source fetched.

    Every customer-facing policy document — Consumer ToS, Privacy Policy, Commercial ToS, Usage Policy, and any AI-specific addenda — is fetched automatically three times per week.

  2. 02

    Clauses extracted.

    Each document is split into clauses by paragraph and section, mapped to the six surfaces, and stored with its verbatim quote and a deep link to the exact section it came from.

  3. 03

    Clauses scored.

    Each clause is evaluated by the reasoning engine against the five questions, and the deterministic decision table computes the rating. Example — Claude (Anthropic): Rating MED, driver “Outputs limited to non-commercial use in evaluation context.”

  4. 04

    Published and monitored.

    The record is published with verbatim quotes, citations, the computed rating, and an auto-generated driver. Documents are re-crawled three times per week; any change re-evaluates the affected clauses and appears in the Updates feed within 24 hours.

↳ DETERMINISM

Ratings are computed, not editorialized.

The reasoning engine runs at a fixed temperature, so the same clause yields the same answer on every run. The decision table above is the entire rating logic — there are no manual overrides. Sponsors have no influence over ratings.

↳ NOT LEGAL ADVICE

This is a public record, not counsel.

AIPolicyCompare is informational. Findings are summaries of public policy language and do not constitute legal advice. Before relying on a finding for a contractual decision, consult counsel.

↳ GRC AUDIT STANDARDS

Our Rigorous 3-Pass Verification SOP

To ensure 100% auditability and trust for legal counsel and procurement managers, every vendor review follows a standardized 3-pass extraction and verification process:

PASS 01 · AUTOMATED INGEST

Playwright headless crawlers capture raw text snapshots from live policy URIs. Documents are hashed (SHA-256) to establish an immutable verification baseline.

PASS 02 · CLAUSE EXTRACTION

An extraction engine pulls verbatim clauses, maps them to the six surfaces, and checks each against a 40-character sentinel from the source text for original-source verification.

PASS 03 · AUTOMATED VERIFICATION

A second automated pass re-checks every citation against the stored snapshot and validates its exact source coordinates before the record is published. No human edits the ratings; they are computed, not editorialized.

Which surfaces drive the rating

We don't blend the six surfaces into a weighted average — the overall rating is set by the single most severe clause (the rules above). But the surfaces aren't equal in what counts as severe: a broad grant over your prompts or outputs, or training on your inputs, jeopardizes your IP most directly, so the HIGH/MED thresholds are strictest there.

In rough order of how often they drive a MED or HIGH for the buyers we serve:

1 · Ownership
Prompt & output grants
2 · Training
Training on inputs & opt-out
3 · Retention
How long inputs are kept
4 · Commercial
Limits on using outputs
↳ FOUND AN ERROR?

If we got something wrong, we want to know.

Every record has a “submit a correction” link. Substantiated corrections are credited in the record’s history.

📢 POLICY UPDATES ALERT

AI Policy Intelligence Brief

Built for compliance officers, legal counsel, and SaaS founders. Join the early-access list — we'll email you when it launches. It will track high-value vendor term changes, training policy updates, and risk-rating modifications.