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Services
- Data
- AI
  - Artificial Intelligence
  - Prompt Engineering
- Digital Engineering
  - Quality Assurance Services
  - Full Stack Development
- Graph
  - Knowledge Graphs
  - GraphRAG
Solutions
- AI-ready Data Enablers
- Use Cases
- By Industry
- Products & Accelerators
  - Datavid Rover
  - Trust Signals
Resources
Company
- About Us
- Careers

Protect your journal’s integrity with Trust Signals

Trust Signals produces a single, explainable Trust Score backed by verifiable data to flag potential issues like retractions, fake authors, and undisclosed funding.

Trust Signals provides editors with evidence-based insights by analyzing 30+ trust markers to help you vet authors faster and more confidently.

Why it matters

Editors no longer need to rely on intuition or manual checks. Trust Signals transforms metadata into a transparent confidence score you can cite, share, and defend — helping you protect your journal’s reputation, prioritize editorial review, and streamline peer review.

How Trust Signals works

Using verifiable research metadata and adaptive scoring, we assess manuscripts across four dimensions to produce a single, explainable Trust Score
(0–100). Topic alignment and collaboration network analysis reveal patterns beyond the manuscript — so you can quickly identify what warrants closer review.

Author credibility & verification

Detects identity mismatches and authorship anomalies to spot paper-mill patterns.

Reference quality & integrity

Flags retracted or circular citations.

Institutional trust & affiliations

Verifies affiliations via ROR and OpenAlex.

Transparency & compliance

Checks funding, open access, and clinical trial disclosures.

Limited Early Access

Shape how integrity is assessed

Join a small group of publishers evaluating how transparent, evidence-based scoring supports editorial decision-making.

The goal:

Screen authors, manuscripts, and references with PID-backed integrity checks (e.g. ORCID, ROR, CROSSREF).
Catch problems before peer review - not after publication.