AI Compliance Vendors

LatticeFlow AI

LatticeFlow AI AG

A single platform to discover, evaluate and govern risk to secure your AI future.

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Last verified April 22, 2026

Quick facts: LatticeFlow AI is an AI compliance vendor founded in 2020 and headquartered in Zurich, Switzerland. The vendor publicly documents coverage for NIST AI RMF, ISO/IEC 42001, and EU AI Act. Pricing is available on request. Profile last verified April 22, 2026, with every claim traceable to a cited public source.

About LatticeFlow AI

LatticeFlow AI is a Swiss deep-tech company headquartered in Zurich, spun out of ETH Zurich in 2020, that provides a platform for AI security and governance centered on deep technical evaluations. The company co-created COMPL-AI, the first open-source evaluation framework mapping EU AI Act requirements to concrete technical controls for generative AI, in partnership with ETH Zurich and INSAIT. This positions LatticeFlow AI as a primary reference for EU AI Act compliance-centered AI assessments. The platform covers agentic AI risk assessment, foundation model risk screening, automated AI security red-teaming, and continuous AI governance operations. It is listed in the 2025 Gartner Market Guide for AI Governance Platforms and the 2025 Gartner Market Guide for AI TRiSM. Customers include global wealth management institutions, Axpo (energy), defense organizations, and Swiss Federal Railways.

Frameworks supported

Regulations and voluntary standards LatticeFlow AI documents support for on their own materials. Chip shading reflects the strength of the claim, not an independent audit.

NIST AI Risk Management Framework

Voluntary standard · US · voluntary

Full
ISO/IEC 42001:2023 AI Management System

Voluntary standard · Global · voluntary

Full
EU Artificial Intelligence Act

Regulation · EU · in force

Full

LatticeFlow AI features

Capabilities LatticeFlow AI markets publicly. Inclusion means the feature is documented on the vendor's site — not that it's best-in-class. Last verified April 22, 2026.

AI Model Inventory

Centralized registry of all AI/ML models in use across the organization, with ownership, lifecycle stage, and risk classification.

Policy Management

Authoring, versioning, and distribution of AI usage policies mapped to regulations.

Risk Assessment Workflow

Guided workflows for completing AI impact assessments, risk scoring, and approval routing.

Bias & Fairness Testing

Automated statistical testing for disparate impact across protected attributes, with audit-ready reports.

Explainability

SHAP, LIME, counterfactual, and feature-importance explanations for model decisions.

Model Monitoring

Production monitoring for performance, drift, data quality, and fairness regressions.

LLM Red Teaming

Automated adversarial testing of LLMs for jailbreaks, prompt injection, and unsafe outputs.

Audit Evidence Collection

Automated collection, hashing, and retention of evidence (model cards, test results, approvals) for audit.

Regulatory Intelligence

Ongoing tracking of AI laws, standards, and enforcement, mapped to your model inventory.

Integrations

Documented by LatticeFlow AI in public product materials.

  • OpenAI API
  • GitHub

LatticeFlow AI pricing

No public pricing. Enterprise platform sold via direct sales. Contact sales for demo and pricing.

Frequently asked

What is LatticeFlow AI?+

LatticeFlow AI is a AI governance platform headquartered in Zurich, Switzerland, founded in 2020. Profile last verified April 22, 2026.

How much does LatticeFlow AI cost?+

LatticeFlow AI does not publish pricing. No public pricing. Enterprise platform sold via direct sales. Contact sales for demo and pricing.. Verified April 22, 2026.

Which AI compliance frameworks does LatticeFlow AI support?+

LatticeFlow AI documents support for NIST AI RMF, ISO/IEC 42001, and EU AI Act in its public materials. Coverage strength varies — see the framework chips above.

Who is LatticeFlow AI for?+

LatticeFlow AI markets to Financial Services, Defense & National Security, and SaaS & Technology teams. Match it against your specific framework and integration requirements before committing.

Sources

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