Screener/Deeplify

Deeplify

Industrial AI for safety-critical infrastructure inspection, directly reducing physical risk in energy and manufacturing.

HQ🇩🇪 DE
Est2023
Size1-10
deeplify.de
Score
31.0 / 100
Evidence
3 items
Confidence
low

Early-stage safety posture - basic practices exist but significant gaps remain.

Weaknesses:Governance Maturity, Technical Safety, Risk Assessment, Regulatory Readiness, External Engagement
Focus Areas
industrial ainon-destructive testingcomputer visiondefect detectionenergy infrastructure

Strengths

No notable strengths identified

Risks

  • Engagement score (20) - significant gap
  • Regulatory score (25) - significant gap
  • Governance score (30) - significant gap
  • Low evidence coverage (3 items)
  • Risk score (35) - significant gap
Table of Contents

Security Assessment

Security-relevant indicators for vendor evaluation

Security Posture
40
TS-01dim: 45
Red Teaming & Pre-deployment Testing
Adversarial testing before deployment
TS-05dim: 45
Robustness & Adversarial Resilience
Resistance to adversarial attacks
RA-01dim: 35
Sector-Specific Risk Assessment
Risk analysis for deployment context
RA-03dim: 35
Dual-Use & Misuse Risk
Dangerous capability awareness
RA-07dim: 35
Incident History & Track Record
Past incidents and response quality
EE-04dim: 20
Vulnerability Disclosure Program
Bug bounty or CVE reporting process
Incident History
Deeplify incident records sourced from AIAAIC Repository and public reporting.
Integration: AIAAIC, OECD AI Incidents Monitor
Third-Party Audits
External audit reports, SOC 2 attestations, and ISO certifications verified where published.
Sources: Company filings, registry lookups
CVE & Disclosures
Known vulnerabilities and security advisories from NVD, GitHub Security Advisories, and vendor pages.
Sources: NVD, GHSA, vendor disclosure pages

Dimension Breakdown

GM
Governance Maturitypreliminary
Published policies, corporate structure, safety mandate, whistleblowing, executive commitment.
30
TS
Technical Safetypreliminary
Benchmarks, adversarial robustness, fine-tuning safety, watermarking, model cards, research output.
45
RA
Risk Assessmentpreliminary
Dangerous capability evaluations, thresholds, external testing, bug bounty, halt conditions.
35
RR
Regulatory Readinesspreliminary
ISO 42001, EU AI Act compliance, GPAI obligations, international commitments, incident reporting.
25
EE
External Engagementpreliminary
Survey participation, research support, transparency, behavior specs, open-source contributions.
20

Social Impact & Safety Profile

Emerging

Deeplify applies computer vision and deep learning to non-destructive testing (NDT), automating defect detection in pipelines, turbines, and industrial components. First product customer is Open Grid Europe (Germany's largest gas transmission operator). Founded by a physicist (CEO), energy industry veteran from BP (COO), and robotics/AI researcher from TU Munich and ETH Zurich (CTO). Pre-seed funded at EUR 2M by D11Z Ventures, Vanagon Ventures, and EWOR.

industrial safetyinfrastructure inspectiondefect detectionenergy sector ai

Peer Comparison

AI Underwriting Company
A-70

Governance Tooling

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Gray Swan
B+64.7

Evaluations & Benchmarking

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Haize Labs
B56.7

Evaluations & Benchmarking

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FID Labs
D-20

Robustness & Adversarial

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Data Sources & Methodology

Scoring methodology v0.1 · 40 indicators · 6 frameworks

Last assessment: 2026-04-02 · Confidence: low · Evidence: 3 items

NIST AI RMF · EU AI Act · ISO 42001 · FLI AI Safety Index · MLCommons AILuminate · METR

How is this company scored? →Full methodologyView in Screener

Scores reflect publicly available information. A low score may indicate limited transparency rather than poor safety practices.