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As Artificial Intelligence (AI) becomes more pervasive in industries like cybersecurity, identity management and data governance, the question of trust remains central. How can organizations trust that the AI solutions they use, especially in critical areas like Identity Management, will handle their sensitive data responsibly? The key to building trust in AI lies in one transformative approach: RAG (Retrieval-Augmented Generation) and the use of company documents. Let’s explore how this innovation is reshaping the trust landscape in AI.<h3>How IAMONES Leverages RAG and Company Documents </h3>At IAMONES, we’ve adopted RAG to push the boundaries of what's possible in Identity Governance and Administration (IGA). In traditional IGA platforms, implementing risk policies and configuring the system requires manual configuration and deep technical expertise. Current platforms often rely on complex rule-based engines, technical jargon, and predefined workflows, making them inaccessible to non-technical stakeholders. However, with the integration of Large Language Models (LLMs) and RAG, IAMONES has transformed this process by enabling natural language interactions, simplifying the complexity of identity management. Here’s how IAMONES is innovating the space with RAG:1. Natural Language Configuration: Instead of configuring risk policies through cumbersome interfaces, IAMONES allows users to define and implement these policies using everyday language, just in a document;2. Dynamic Risk Assessment: IAMONES leverages RAG to perform dynamic risk assessments based on the latest information available in company records and security reports.By combining the capabilities of LLMs with context-specific data retrieval through RAG, IAMONES provides a transformative solution for organizations seeking a more intelligent, intuitive, and transparent approach to identity management.

How can we trust AI?

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As AI becomes integral in cybersecurity and AIM (Artificial Intelligence for Identity Management), concerns about data privacy grow.&nbsp; Companies wonder: Are AI providers stealing our data? Let’s explore how leading LLM providers OpenAI, Anthropic, and Mistral handle your data.<h2>What Happens with Your Data?</h2>Using AI via APIs raises valid privacy concerns. But, with OpenAI, Anthropic, and Mistral, these fears are often exaggerated. Here’s the truth:<h3>OpenAI </h3><ul><li>No Data Usage for Training: Your API data isn’t used for training unless you opt-in;</li><li>Retention Policy: Data is kept for up to 30 days, with an option for zero retention;</li><li>Deletion Control: You can request data deletion, processed within 30 days.</li></ul><h3>Anthropic</h3><ul><li>Strict No-Training Policy: API data isn’t used for training, unless explicitly agreed;</li><li>Custom Retention: Data is retained based on your contract, with flexible deletion options.</li></ul><h3>Mistral</h3><ul><li>No Data Exploitation: API data isn’t used for training; it’s strictly for your usage;</li><li>Clear Data Handling: Their policies ensure transparency and control over your data.</li></ul><h2>How IAMONES Ensures Your Data Privacy</h2> At IAMONES, we understand that your data is sensitive and must be handled with care, especially in IAM and cybersecurity applications. Our platform leverages LLMs to provide advanced Identity Management solutions without compromising your data’s security. We ensure that your data is used solely for the intended purpose, with no risk of it being shared or used to train external models. Your trust and data privacy are at the core of what we do. The idea that AI companies are 'stealing' your data is mostly a myth. Companies like OpenAI, Anthropic, and Mistral take stringent measures to protect your data, ensuring it remains secure, private, and under your control. When you partner with IAMONES, you gain the benefits of advanced AI without sacrificing data security.<table style="border-collapse: collapse; width: 100%;" border="1" data-mce-style="border-collapse: collapse; width: 100%;" data-mce-selected="1"><tbody><tr style="border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="border-color: #ba372a; border-style: solid;"><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">Company</td><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">Training Data Usage?</td><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">Data Retention</td><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">User-Controlled Deletion</td></tr><tr style="border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="border-color: #ba372a; border-style: solid;"><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">Open AI</td><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">No, unless opted-in</td><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">30 days max, zero option</td><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">Yes, within 30 days</td></tr><tr style="border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="border-color: #ba372a; border-style: solid;"><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">Anthropic</td><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">No, unless agreed otherwise</td><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">As per contract</td><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">Yes, per contract</td></tr><tr style="border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="border-color: #ba372a; border-style: solid;"><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">Mistral</td><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">No</td><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">User-controlled</td><td style="width: 25%; border-color: rgb(186, 55, 42); border-style: solid;" data-mce-style="width: 25%; border-color: #ba372a; border-style: solid;">Yes</td></tr></tbody></table>References:https://platform.openai.com/docs/modelshttps://openai.com/enterprise-privacy/https://support.anthropic.com/en/articles/7996875-can-you-delete-data-that-i-sent-via-apihttps://help.mistral.ai/en/articles/156194-does-mistral-ai-exploit-users-data-to-train-its-models

Are They Stealing Our Data?

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Back in June, IAMONES project was showcased at the KuppingerCole EIC Conference 2024 in Berlin. The event brought together experts in identity and access management from around the world.&nbsp;IAMONES plans to build on the momentum from the conference. We are committed to staying at the forefront of the identity and access management industry. Our focus will remain on developing innovative solutions that address the evolving needs of our clients.Watch out the video to know more on our project and get some insights about our name!<figure id="figure-85ln99ub3qm051733w"><iframe id="85ln99ub3qm051733w" src="https://www.youtube.com/embed/kpkRbK4b6u4" class="w-full bg-gray-100 rounded-sm md:rounded-md lg:rounded-lg" style="aspect-ratio: 16/9;" allowfullscreen="" data-url="https://youtu.be/kpkRbK4b6u4" data-corners="default" data-fullwidth="false" data-mce-src="https://www.youtube.com/embed/kpkRbK4b6u4" data-mce-style="aspect-ratio: 16/9;"></iframe></figure>

IAMONES shines at KuppingerCole EIC Conference 2024 in Berlin

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Large Language Models (LLM) can powerfully translate and reason using Natural Language. As such, they are a prominent ingredient for reshaping and simplifying Identity Governance and Administration (IGA). IGA is all about translating technical jargon (IT accounts, applications, and permissions) into comprehensible business terms.Here's a list of major IGA pain points and how Large Language Models can significantly disrupt the ‘old ways’ of doing things in this critical security domain.<table style="border-collapse: collapse; width: 100%;" border="1" data-mce-style="border-collapse: collapse; width: 100%;" data-mce-selected="1"><tbody><tr><td style="width: 50%;" data-mce-style="width: 50%;"> </td><td style="width: 50%;" data-mce-style="width: 50%;"> </td></tr><tr><td style="width: 50%;" data-mce-style="width: 50%;"><h3>Traditional IGA</h3></td><td style="width: 50%;" data-mce-style="width: 50%;"><h3>LLM-powered IGA</h3></td></tr><tr><td style="width: 50%;" data-mce-style="width: 50%;">Users with complex IGA User Experiences are "lost in translation", constantly asking for IT support.</td><td style="width: 50%;" data-mce-style="width: 50%;"> Users ask questions in their natural language, their mother tongue. They no longer require IT support, and IT no longer has to offer multi-language UIs. It’s the Extinction of the “Painful User Experience" age when Humans had to adapt to Software. Now, Software adapts to Humans.</td></tr><tr><td style="width: 50%;" data-mce-style="width: 50%;">Policies, workflows and other instructions must be hard coded – either writing Software Software or implementing very technical product configurations.</td><td style="width: 50%;" data-mce-style="width: 50%;">Policies, workflows, and other instructions are given in Natural Language without any further coding needed. Auditors are happier, too, as they can finally audit what they understand.Stop spending money on IGA software configurations.</td></tr><tr><td style="width: 50%;" data-mce-style="width: 50%;">The Wealth of Identity Governance-related documental Knowledge (e.g., homegrown application descriptions, Risk Policies, Organizational who's who) is on the shelf and not leveraged for IGA implementations.</td><td style="width: 50%;" data-mce-style="width: 50%;"> Large Language Models can «learn and resonate»&nbsp; from PDF/Word documents. As an ‘IGA expert’, they can learn from your documents and use this knowledge to analyze your Identity Data.&nbsp; It’s the demise of RBAC/ABAC.</td></tr></tbody></table><h3>&nbsp; &nbsp; &nbsp; &nbsp; "Everything as Natural Language"</h3> &nbsp;

Revolutionizing Identity Governance: How Large Language Models are Breaking the Mold

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How can we trust AI?

Are They Stealing Our Data?

IAMONES shines at KuppingerCole EIC Conference 2024 in Be...

Revolutionizing Identity Governance: How Large Language M...