As AI continues to embed itself deeper into business processes, the conversation is shifting from excitement to responsibility. While tools like large language models (LLMs) and AI agents are transforming how we interact with data, they also raise new challenges ranging from data breaches and regulatory violations, to accessing and sharing sensitive information.
At Infotechtion, we’ve developed the i-ARM platform to help organizations manage this delicate balance. Designed for secure, compliant, and scalable AI governance, i-ARM brings together microservice architecture, intelligent data classification, and deep integration with Microsoft Purview.
But how does it all work under the hood?
A Modular Architecture Built for Scale
i-ARM is built using a microservices approach, where each function runs independently but contributes to a unified data model. This means teams can update or scale individual components without disrupting the entire system – crucial when you’re adapting to evolving AI risks and regulations.
Smarter Classification with AI Models
At the core of i-ARM is its data classification engine, which combines rules-based logic and AI classifiers. This hybrid model allows us to accurately identify sensitive content, including medical and personal data, while also learning from context. Classification isn’t just for tagging; it can trigger automated actions like security policy enforcement, data retention rules, or alerts to the SOC team.
Governance Meets Action: Purview Integration
Microsoft Purview plays a critical role in our governance stack. By embedding the Purview SDK, we ensure that all AI interactions (internal or third-party) are tracked, discoverable, and policy-bound. This closes a major visibility gap for many enterprises using generative AI tools.
Embedding Microsoft Purview SDK into Infotechtion’s AI governance solution improved trust and security by aligning Gen-AI interactions with Microsoft Purview’s enterprise policies. – Vivek Bhatt, CTO Infotechtion.
What’s Next: Conversational Governance with LLMs
Looking ahead, we’re building an interactive data bot interface that lets auditors and stewards ask questions directly from the governance platform and receive answers or visuals in return. This taps into the power of LLMs with Azure Foundry offering a robust platform to host and scale these models for real-time performance. With Azure Foundry, we’re leveraging its advanced cloud infrastructure to fine-tune LLMs for i-ARM, enabling real-time processing and model customization tailored to specific governance needs. Think faster response times and adaptive learning from enterprise data. Not just for classification, but also for reasoning and interaction.
We’re also exploring agentic AI, where AI systems can take safe, pre-approved actions on behalf of users. Imagine a data steward asking, “Delete all ROT files older than 5 years,” and the system executes it instantly with full auditability.
Final Thoughts
In a world of growing AI complexity and tighter regulations (EU AI Act, ISO/IEC 42001), responsible AI isn’t optional—it’s a foundation. Platforms like i-ARM are helping organizations shift from reactive compliance to proactive, transparent AI governance.
Whether you’re exploring LLMs or already running AI agents in production, aligning with robust governance frameworks is key. i-ARM provides a blueprint.
Stay tuned for more updates as Infotechtion continues to innovate and enhance its i-ARM service. Contact us today at contact@infotechtion.com to get started on your safe and responsible AI adoption journey to make sure you are ready for your workplace needs.
