AI Compliance Vendors

Giskard vs LatticeFlow AI

Side-by-side comparison of framework coverage, pricing, capabilities, and target customers. Last checked September 2026.

Canonical URL: https://aicompliancevendors.com/compare/giskard-ai-vs-latticeflow-ai

Giskard

European platform for red teaming, evaluating and guarding AI agents, with an Apache 2.0 open-source library and on-premise deployment

Giskard is a Paris-based company founded in 2021 by Alex Combessie, Jean-Marie John-Mathews and Andrei Avtomonov. Combessie and John-Mathews are now co-CEOs, and Giskard says its co-founders previously built AI systems at Dataiku and Thales. It sells software and services for testing and securing LLM agents. Its first funding round, €1.5 million led by Elaia with Bessemer Venture Partners, was announced in December 2022. Giskard says it also received a €3 million strategic investment through the European Commission's EIC Accelerator in 2023 and a €3 million Bpifrance grant in 2024 for LLM evaluation research with Mistral AI, Artefact, INA and BnF. CORDIS lists a €2.5 million EU contribution to its EIC project, which ran from September 2023 to August 2025. Giskard Hub is the paid platform. Continuous red teaming runs multi-turn attacks that adapt to the agent's answers, generated from the company's own documents and knowledge bases. It tests for hallucinations, stereotypes and discrimination, harmful content, disclosure of personal information and prompt injection. Testing is black-box: the agent only needs an API endpoint, and coverage is limited to text-to-text conversational agents. The Hub also schedules agent evaluations and manages test datasets, custom checks and human review, with alerts, SSO, role-based access and audit logs. It runs as SaaS, in a private cloud or on premises, with EU or US data processing. Giskard Guards, launched in April 2026, is a runtime guardrail layer that runs in the customer's infrastructure. It inspects prompts, responses, tool calls and multi-step reasoning, and its policies are written as code in OPA/Rego. Giskard also sells AI security audits that end in a go/no-go report, and it is offering a free trial of a new Agentic Red Teamer to a limited number of users. The open-source library is Apache 2.0 licensed. Version 3, a rewrite for multi-turn agent testing, became stable in August 2026. Version 2 is no longer actively maintained, and tabular models have no v3 equivalent. Giskard also publishes Phare, an LLM safety benchmark launched in February 2025 with Google DeepMind as research partner. Logos on its site include BNP Paribas, AXA, BPCE, Société Générale, Crédit Agricole, Michelin, Decathlon, L'Oréal and Doctolib. **AI compliance coverage** Guards includes an EU AI Act policy pack for prohibited practices such as social scoring and real-time biometric identification, and Giskard says Guards covers OWASP LLM risks. It doesn't map its products to the NIST AI RMF or ISO 42001. Its trust center, run on Bastion, lists GDPR and a SOC 2 Type 2 report and shows HIPAA as in progress. **Who it's for** Enterprises, especially in European banking and insurance, that run customer-facing LLM agents and want testing and runtime controls they can deploy on premises.

Last checked October 15, 2026Paris, France

LatticeFlow AI

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

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.

Last checked September 21, 2026Zurich, Switzerland

What the data shows

We haven't published an editorial verdict on this pair yet. The comparison below is built from public vendor materials and our taxonomy — no editorialized ranking.

  • Shared framework coverage: EU AI Act
  • Only Giskard covers: SOC 2
  • Only LatticeFlow AI covers: ISO/IEC 42001, NIST AI RMF
  • Shared capabilities: 2 of 18 listed.

Want our editorial take? Email the editors or read our methodology.

At a glance

AttributeGiskardLatticeFlow AI
Founded20212020
HeadquartersParis, FranceZurich, Switzerland
EmployeesUndisclosed11-50
Funding€1.5M first round led by Elaia (December 2022), plus a €3M EIC Accelerator investment (2023) and a €3M Bpifrance research grant (2024), per GiskardSeries A, $12M raised (October 2022), led by Atlantic Bridge and OpenOcean with participation from FPV Ventures. Prior seed of $2.8M (January 2021).
PricingNo prices are published. Two plans: Open-source, a free Python library for local agent experiments with community support, and Professional, quoted on request ('Get your AI audited'). Professional adds automated audits with 50+ adversarial probes, evaluation dataset generation, SSO and role-based access, CI/CD integration through the SDK, on-premise, private cloud or SaaS deployment, and support with SLAs. Advisory on fixes and guardrails is an extra service. Giskard advertises a free Agentic Red Teamer trial with limited spots and an offer for startups and small teams, without stating terms for either.No public pricing. Enterprise platform sold via direct sales. Contact sales for demo and pricing.
WebsiteVisit siteVisit site

Framework coverage

FrameworkGiskardLatticeFlow AI
EU AI ActlimitedFull
ISO/IEC 42001—Full
NIST AI RMF—Full
SOC 2Certified—

Capabilities

CapabilityGiskardLatticeFlow AI
AI Guardrails✓—
AI Model Inventory—✓
Agentic Red Teaming✓—
Audit Evidence Collection—✓
Audit Logging✓—
Bias & Fairness Testing✓✓
Data Leakage Prevention✓—
Explainability—✓
Hallucination Detection✓—
Human-in-the-Loop✓—
LLM Evaluation✓—
LLM Red Teaming✓✓
Model Monitoring—✓
Policy Enforcement✓—
Policy Management—✓
Prompt Injection Defense✓—
Regulatory Intelligence—✓
Risk Assessment Workflow—✓

Industries served

Giskard

  • Financial Services
  • Insurance

LatticeFlow AI

  • Financial Services
  • Defense & National Security
  • SaaS & Technology

Integrations

Giskard

  • LiteLLM
  • OpenAI API
  • Anthropic API

LatticeFlow AI

  • OpenAI API
  • GitHub

Frequently asked

What is the difference between Giskard and LatticeFlow AI?+

Giskard is European platform for red teaming, evaluating and guarding AI agents, with an Apache 2.0 open-source library and on-premise deployment; LatticeFlow AI is A single platform to discover, evaluate and govern risk to secure your AI future. The full side-by-side covers framework coverage (1 shared, 1 unique to Giskard, 2 unique to LatticeFlow AI), pricing model, and capability overlap.

How do Giskard and LatticeFlow AI pricing compare?+

Giskard: No prices are published. Two plans: Open-source, a free Python library for local agent experiments with community support, and Professional, quoted on request ('Get your AI audited'). Professional adds automated audits with 50+ adversarial probes, evaluation dataset generation, SSO and role-based access, CI/CD integration through the SDK, on-premise, private cloud or SaaS deployment, and support with SLAs. Advisory on fixes and guardrails is an extra service. Giskard advertises a free Agentic Red Teamer trial with limited spots and an offer for startups and small teams, without statin

Which AI compliance frameworks do Giskard and LatticeFlow AI both support?+

Both vendors document support for EU AI Act. Coverage strength varies; see the framework matrix below.

Related

Editorial independence: This comparison is free and was not paid for by either vendor. See our methodology.