Generative AI has the potential to transform how businesses operate, but there’s a catch—it’s only as good as the data behind it. If your AI model is working with outdated, unstructured, or poorly classified data, don’t be surprised when the results are generic, inaccurate, or even misleading.
That’s where data curation comes in.
In our new white paper, "Leveraging Generative AI to Transform Your Business," created in partnership with Clarion AI Partners, we explore why organizations must focus on discovery, classification, and governance before expecting game-changing AI outcomes.
The Problem with Unstructured Data
Most organizations sit on mountains of unstructured data—old reports, emails, presentations, and contracts—scattered across different systems. Without a clear strategy to identify what’s valuable (and what’s just digital clutter), AI models end up pulling from a messy, unreliable data pool—a pool of dark data.
At ActiveNav, our mission is to drive organizations toward zero dark data, ensuring that every piece of content is classified, accessible, and AI-ready. By eliminating dark data, companies gain better insights, reduce risk, and fully unlock AI’s potential.
The Solution: Smarter Data Management
A Retrieval Augmented Generation (RAG) approach helps AI models retrieve high-quality, curated information, ensuring outputs are accurate and contextually relevant. But for RAG to work, organizations need a strong data foundation—and that means:
- Identifying high-value content that AI can use
- Classifying and enriching data for easy retrieval
- Securing or disposing of sensitive, outdated files
How ActiveNav Can Help
ActiveNav automates data discovery and classification, making it easier to:
- Find and protect sensitive data
- Streamline AI training with high-quality content
- Reduce risk and improve compliance
The future of AI belongs to organizations that control their data—not the other way around. If your AI isn’t delivering the insights you expected, your data may be the issue. Download our white paper to learn how better data leads to better AI—and how to get there.