DetectAI — Licensed Media Detection &
Policy-Grade Enforcement

Spot license violations fast. Prove what happened with audit-ready, chain-of-custody evidence your legal and rights teams can act on. Get paid and stop unlicensed use.
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Why Now?

Platforms strip metadata, AI blurs provenance, and single-signal tools miss edited or derivative media. Rights teams need a unified, trusted view of where assets appear, which sightings break policy, and evidence strong enough for takedowns and recovery.

What DetectAI Does

1. Ingest your reference catalog & license metadata.

2. Search across web, social, and ad networks for matches—including cropped, recolored, or re-encoded variants.

3. Fuse multiple authenticity signals (C2PA, visible/invisible/model watermarks, perceptual fingerprints, telemetry).

4. Score each sighting with a calibrated risk + policy-violation verdict (LLM-as-a-judge with guardrails).

5. Escalate edge cases to expert reviewers; track κ and overturns to keep calibration honest.

6. Deliver evidence bundles (hashes, manifests, logs, screenshots) and trigger takedowns, invoices, or case tickets via API/webhooks.

Diagram step 1: Send your content to the ModerateAI API.

Built for “Policy Violation” Work

We’re policy-to-enforcement veterans. Our platform encodes your licensing terms, usage rights, and partner policies as machine-enforceable rules, then backs every decision with defensible artifacts and human-in-the-loop (HITL) confirmation when needed. Shared platform primitives—HITL Workbench, Evaluator, Policy & Taxonomy Builder, Data Provenance Ledger—come from our safety-grade heritage.

Why TrustLab?

Multi-signal > Single-signal

DetectAI reliably handles transformed media—crop, recolor, re-encode—by fusing C2PA, watermarks, fingerprints, and telemetry instead of relying on brittle hashes.

Evidence that Stands Up

We deliver chain-of-custody bundles with cryptographically verifiable elements and consistent formatting for claims, takedowns, and invoices.

HITL Where It Matters

Gray-zone detections route to expert reviewers with calibration targets (e.g., κ ≥ 0.75; overturn % monitored) so you can trust the calls.

Battle-tested LLM-as-a-Judge

We operationalize LLM evaluators as scalable, application-specific judges: binary criteria, low temperature, structured outputs, and “explain-why” rationales—aligned to human labels and refreshed over time. (Why this works and best practices.)

No-drama Integration

Modular APIs let you start C2PA-only, fingerprint-only, or full fusion; egress to Rightsline, Salesforce, DAM/CMS, SIEM and more.

Security by Default

PII redaction at ingest, hashed identifiers for provenance data, SOC 2/ISO alignment, SSO/SCIM, and on-prem options for sensitive catalogs.

Boost Your Licensing Revenue Drivers

Recall (top-K match):

≥ 90%

False Positive Rate:

≤ 5%

Mean Time to Detection:

≤ 6 hours from sighting → alert

Evidence Completeness

95% of cases include full provenance + logs

Reviewer Agreement

0.75 on gray cases

How DetectAI Works

Ingress

Reference catalogs + license DBs; live crawls; partner feeds (CDN/ad networks); EXIF/C2PA manifests; watermark/fingerprint extractors.

Decisioning

A prompt schema fuses signal features; scores are calibrated (e.g., Brier/ECE) and thresholded for high recall on known assets at low FPR. LLM-as-a-judge applies policy rubrics with JSON verdicts and rationales.

HITL

Risk-tiered queues, adjudication, κ tracking, and dispute workflows ensure consistency and reduce false actions.

Egress

Webhooks/API into rights systems, DAM/CMS, CRMs, and ticketing to automate takedowns, invoices, and case creation—plus exportable evidence PDFs/JSON.

Diagram step 1: Send your content to the ModerateAI API.

Where DetectAI Shines

Stock Libraries &
Studios

Tom Siegel

Find and prioritize high-value unlicensed use; ship invoice + evidence.

Sports & Labels

Tom Siegel

Track derivative clips and remixes across social; escalate borderline “fair use” to experts.

Newsrooms

Tom Siegel

Verify authenticity and lineage pre-publication; flag synthetic or manipulated assets.

Independent Creators &
Agencies

Tom Siegel

Protect flagship campaigns; centralize violations and takedowns.

What You Get on Day 1

Quickstart run on a pilot catalog (connectors + first detections)

Policy mapping workshop to encode your license rules

Live dashboard with risk-ranked sightings and exportable evidence

API keys & integrations to your existing rights ops stack

Plan Options

Pilot

Multi-signal detection

Dashboard

Evidence export

Check Our Performance based on a Free Pilot

Pro

HITL workbench

Adjudication metrics

Advanced integrations

Enterprise

Custom Policies

Enhanced SLAs

Dedicated Support

Ask us for ACV bands based on catalog size and automation level.
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Frequently Asked Questions

What about security and data residency?
Will this work if platforms strip metadata?
Are LLM judges really reliable for policy decisions?
How do you avoid over-blocking or weak claims?

Tell Us Your Top There Assets to Protect

We'll run a targeted crawl, return risk-ranked sightings with evidence, and map the ROI from faster enforcement and recovered licensing value. Let's talk.