# giskard.ai

> AI-optimized mirror of giskard.ai containing 50 pages totalling 50,258 words of clean markdown content, structured data, and semantic HTML. Original source: https://giskard.ai. Last updated: 2026-07-20T14:38:13.151Z.

Each page is available as HTML (with JSON-LD structured data) and Markdown (text-only, ideal for LLMs and RAG).

## Homepage

- [AI Red Teaming & LLM Security Platform | Giskard](/content/site-root.html): Secure AI agents with Giskard’s continuous AI red teaming. Detect vulnerabilities, improve LLM security, and safeguard your AI systems. (834 words)

## Articles & Blog Posts

- [knowledge/guide-to-model-evaluation-eliminating-bias/index.html](/content/knowledge/guide-to-model-evaluation-eliminating-bias/index.html) (1,483 words)
- [Giskard Vision: Enhance Computer Vision models for classification, object & landmark detection](/content/knowledge/assessing-the-quality-of-computer-vision-models-with-giskard-vision.html): Giskard Vision: Automate assessment of Computer Vision models for classification, detection, and landmarks. Identify biases, performance issues, and ethical concerns. (1,392 words)
- [Best AI agent red teaming tools in 2026 to detect vulnerabilities](/content/knowledge/best-ai-agent-red-teaming-tools-in-2026-understanding-features-functions-and-solutions.html): AI Red Teaming tests AI systems by simulating real-world adversarial attacks. Learn about the leading AI red teaming tools and how they detect AI vulnerabilities. (3,789 words)
- [AI phishing attack in Australia: 270,000 fake government emails expose LLM security risks](/content/knowledge/ai-phishing-attack-in-australia-270-000-fake-government-emails-expose-ai-security-gap.html): 270,000 phishing emails impersonating Services Australia show signs of AI generation. Examine how attackers used LLM capabilities to craft convincing scam campaigns. (1,239 words)
- [Giskard's customers and case studies for Agent AI Development](/content/knowledge-categories/case-studies/index.html): Case studies from companies that needed evaluation for their Agentic Quality Testing, AI Red Teaming or other AI use cases. (236 words)
- [Testing LLM business alignment & AI hallucination detection](/content/knowledge/llm-business-alignment-detecting-ai-hallucinations-and-misaligned-agentic-behavior-in-business-systems.html): Test LLM business alignment and detect AI hallucinations in production. Real examples of misaligned agents, hallucination detection methods, and testing frameworks (1,750 words)
- [Advanced Facial Landmark Detection for L'Oréal | AI Evaluation with Giskard](/content/knowledge/loreal-leverages-giskard-for-advanced-facial-landmark-detection.html): Discover how L'Oréal enhances its AI models with Giskard for robust facial landmark detection. Learn about model evaluation techniques & performance metrics (2,177 words)
- [A new look for Sophia: the story behind Giskard’s rebranding](/content/knowledge/a-new-look-for-sophia-the-story-behind-giskards-rebranding.html): From a friendly turtle to a high-tech AI security brand. Read the behind-the-scenes story of Giskard’s rebranding, new logo, and website redesign. (1,568 words)
- [Giskard's retrospective of 2023 and a glimpse into what's next for 2024!](/content/knowledge/2023-in-review/index.html): Retrospective of the last year 2023: covering people, company, customers and product news, and a look into what's next for 2023. (2,440 words)
- [Alex Combessie, Giskard's CEO](/content/team-members/alex-combessie/index.html): Alex Combessie, Giskard's Co-Founder & Chief Executive Officer (854 words)
- [OWASP Top 10 for Agentic Applications 2026: Security Guide](/content/knowledge/owasp-top-10-for-agentic-application-2026/index.html): Explore the OWASP Top 10 for Agentic Applications 2026. Get insights into autonomous agent threats, concrete exploits, and how to secure your AI agents. (1,337 words)
- [OpenAI Atlas browser security risks | LLM vulnerability analysis](/content/knowledge/are-ai-browsers-safe-a-security-and-vulnerability-analysis-of-openai-atlas.html): OpenAI's Atlas browser can read and act across all your tabs. Security researchers have identified architectural LLM vulnerabilities. (1,400 words)
- [Best 7 tools for AI Red Teaming in 2025 to detect AI vulnerabilities](/content/knowledge/best-ai-red-teaming-tools-2025-comparison-features/index.html): AI Red Teaming tests AI systems by simulating real-world adversarial attacks. Learn about the leading AI red teaming tools and how they detect AI vulnerabilities. (1,338 words)
- [Giskard, the leading Quality Assurance platform for Artificial Intelligence models, raises its first financing round to expand its Enterprise offering](/content/knowledge/news-fundraising-2022/index.html): The funding led by Elaia, with participation from Bessemer Venture Partners and notable angel investors, will accelerate the development of an enterprise-ready platform to help companies test, audit & ensure the quality of AI models. (947 words)
- [AI hallucinations and the AI failure in a French Court](/content/knowledge/ai-hallucinations-and-the-ai-failure-in-a-french-court.html): A French court flagged "untraceable" precedents in a recent AI failure. An AI hallucination created false case law, exposing critical failure modes in legal AI. (893 words)
- [AI Safety at DEFCON 31: Red Teaming for Large Language Models (LLMs)](/content/knowledge/ai-safety-defcon-31-red-teaming-llms/index.html): Learn about Generative AI Red team at DEFCON 31's, designed to assess the safety of LLMs from vendors such as OpenAI, Anthropic, Google, and Stability AI. (848 words)
- [Continuous Red Teaming v2026](/content/products/continuous-red-teaming/index.html): Automated AI security testing platform with dynamic multi-turn attacks, context-aware vulnerability detection, and hallucination prevention for LLM agents. (633 words)
- [AI Security and LLM Vulnerabilities](/content/knowledge/a-practical-guide-on-ai-security-and-llm-vulnerabilities.html): Discover the key vulnerabilities in Large Language Models (LLMs) and learn how to mitigate AI risks with clear overviews and practical examples. Stay ahead in safe and responsible AI deployment. (1,256 words)
- [Rabah Abdul Khalek, Giskard's ML Researcher](/content/team-members/rabah-abdul-khalek/index.html): Rabah Abdul Khalek, Giskard's Machine Learning Researcher (173 words)
- [Favour Kelvin, Data Scientist](/content/team-members/favour-kelvin/index.html): Favour Kelvin, Data Scientist | Giskard's Write for the Community (86 words)
- [Real-Time LLM Guardrails vs Batch Evaluations: Complete AI Testing Strategy Guide 2025](/content/knowledge/real-time-guardrails-vs-batch-llm-evaluations/index.html): Learn when to use real-time LLM guardrails vs batch evaluations for AI testing. Complete guide to building comprehensive AI safety strategies in 2025. (830 words)
- [LLM Evaluation Platform | Giskard AI Agent Testing](/content/products/llm-evaluation/index.html): Continuously test and secure LLM agents with automated quality & security vulnerability detection. Prevent hallucinations, security issues, and regressions before production. (805 words)
- [AI Liability in the EU: Business guide to Product (PLD) and AI Liability Directives (AILD)](/content/knowledge/ai-liability-in-the-eu-business-guide-to-product-pld-and-ai-liability-directives-aild.html): EU's AI liability regulations: Learn how Product (PLD) and AI Liability Directives (AILD) will impact your business, and how to ensure AI compliance. (1,327 words)
- [Giskard Guards: Context-Aware AI Guardrails for Agents](/content/products/guards/index.html): Protect AI agents with policy-driven guardrails. Context-aware detection, agentic workflows, EU-sovereign deployment. Stop false positives & real attacks. (483 words)
- [Legal | Giskard AI Testing Platform](/content/legal/index.html): Access Giskard's legal documents, terms and conditions, security policies, trust center, privacy policy, and cookie policy for our AI testing platform. (111 words)
- [team-members/angelo-pedraza-sedano/index.html](/content/team-members/angelo-pedraza-sedano/index.html) (102 words)
- [team-members/mostafa-ibrahim/index.html](/content/team-members/mostafa-ibrahim/index.html) (103 words)
- [Pierre Le Jeune - Lead Machine Learning Researcher](/content/team-members/pierre-le-jeune/index.html): Pierre Le Jeune - Lead Machine Learning Researcher at Giskard (115 words)
- [Jean-Marie John-Mathews, Giskard's CPO](/content/team-members/jean-marie-john-mathews/index.html): Jean-Marie John-Mathews, Giskard's Co-Founder & Chief Product Officer (550 words)
- [Weixuan Xiao - Machine Learning Engineer at Giskard](/content/team-members/weixuan-xiao/index.html): Weixuan Xiao - Machine Learning Engineer at Giskard (170 words)
- [Benoît Malézieux - Machine Learning Researcher](/content/team-members/benoit-malezieux/index.html): Benoît Malézieux - Machine Learning Researcher at Giskard (140 words)
- [LLM Cost | Managing Inference Spend](/content/glossary/llm-cost/index.html): LLM cost covers token pricing, caching, routing, and architecture choices that drive the price of running language models. (104 words)
- [Articles on Agentic Quality Testing and AI Red Teaming](/content/knowledge-categories/blog/index.html): Learn why Evaluations and Quality Testing matters to Agent Developers (6,833 words)
- [Mykyta Alekseiev - ML Engineering Intern at Giskard](/content/team-members/mykyta-alekseiev/index.html): Mykyta Alekseiev - ML Engineering Intern at Giskard (139 words)
- [team-members/sagar-thacker/index.html](/content/team-members/sagar-thacker/index.html) (239 words)
- [Javier Canales Luna - Law and Policy Writer](/content/team-members/javier-canales-luna/index.html): Javier Canales Luna - Law and Policy Writer (378 words)
- [AI researcher- Giskard](/content/team-members/etienne-duchesne/index.html) (52 words)
- [AI Security & Machine Learning Glossary | Giskard](/content/glossary/index.html): Explore Giskard’s glossary of AI red teaming, LLM security, evaluation, threat modeling, and machine learning terms to understand AI risks and defenses. (10,152 words)
- [Alexandre Foucher- Giskard](/content/team-members/alexandre-foucher/index.html): Alexandre Foucher- Customer Success Manager at Giskard (49 words)
- [David Mercado](/content/team-members/david-mercado/index.html): David Mercado - Product Manager at Giskard (99 words)
- [Happiness Omale - Technical writer](/content/team-members/happiness-omale/index.html): Happiness Omale - Technical writer (121 words)
- [Andrei Avtomonov, Giskard's CTO](/content/team-members/andrei-avtomonov/index.html): Andrei Avtomonov, Giskard's Co-Founder and Chief Technical Officer (99 words)
- [Instruction Tuning | Teaching LLMs to Follow Instructions](/content/glossary/instruction-tuning/index.html): Instruction tuning fine-tunes LLMs on instruction–response pairs so they follow user requests more reliably. (96 words)
- [Stéphane Changarnier - Front end design engineer](/content/team-members/stephane-changarnier/index.html): Stéphane Changarnier - Front end design engineer at Giskard (45 words)
- [François Chaulin- Giskard](/content/team-members/francois-chaulin/index.html): François Chaulin- Enterprise Account Executive at Giskard, ex AWS (48 words)
- [Princy Pappachan](/content/team-members/princy-pappachan/index.html): Our first data scientist, Princy Pappachan (89 words)
- [METEOR Score | Machine Translation Evaluation Metric](/content/glossary/meteor-score/index.html): METEOR evaluates machine translation by aligning hypotheses to references with stemming and synonymy, balancing precision and recall. (69 words)

## About Pages

- [About Giskard | AI Red Teaming & LLM Security Platform](/content/about/index.html): Learn about Giskard's mission to secure conversational AI. Our platform delivers AI red teaming, LLM evaluation, and vulnerability scanning. (179 words)
- [Contact Giskard | AI Testing Platform Demo & Support](/content/contact/index.html): Talk to our team about continuous red teaming and LLM evaluation. Trusted by enterprise AI teams at AXA, BNP Paribas, Michelin, Société Générale, and more. (58 words)

## Resources

- [Full Page Index](/index.html): Browse all cached pages with rich metadata
- [About This Cache](/content/about.html): Methodology, technical details, and usage guidelines
- [XML Sitemap](/sitemap.xml): Machine-readable sitemap for crawler discovery
- [Robots.txt](/robots.txt): Crawler directives