The most valuable data in your company isn't missing. It's disconnected.

In today's data-driven world, the urgency to harness unstructured data has never been greater. A staggering 80% of enterprise data resides in formats like emails, contracts, call transcripts, and PDFs, which traditional databases struggle to process. This unstructured data is not overlooked due to its lack of value, but rather because establishing reliable connections to existing structured systems is a formidable challenge. Many organizations possess the data required for effective AI implementation, yet a significant number of AI projects fail to achieve their intended outcomes. A critical factor contributing to this issue is the disconnect between valuable information and the systems that AI relies on. Essential insights about customers, suppliers, products, and risks are often locked away in unstructured formats. As businesses increasingly adopt AI technologies, the absence of this context has become a notable hurdle. Even the most advanced AI models can yield incomplete results if they lack comprehensive knowledge. Success in AI isn't solely about having the most sophisticated algorithms; it hinges on providing AI with a rich, real-time, 360-degree view of the organization, which includes a wealth of unstructured data. The reality is that most vital business interactions occur in natural language rather than in structured formats. Sales representatives communicate through emails, lawyers draft contracts in free text, and customers articulate issues in their own words—all of which generates unstructured data. Over recent decades, as companies transitioned to digital operations, they focused on capturing transactional and financial data, often neglecting the nuanced narratives that provide deeper insights into their operations. Ironically, as enterprises became more digitized, they also generated more unstructured data. While AI technologies have altered the economic landscape, they have not changed the fundamentals of data management. AI models can analyze unstructured data, but they require a clean and connected context to be truly effective. Without timely and reliable context, AI systems risk producing erroneous conclusions or missing crucial nuances. The transformation lies not just in analyzing unstructured data but in integrating it within a sophisticated data architecture. This integration enriches structured data with narrative context, enabling AI systems to operate effectively and consistently. Reltio, a company specializing in context intelligence, has created innovative solutions that allow enterprises to incorporate unstructured data into an intelligent data graph. This approach results in the formation of comprehensive 360-degree profiles for various entities. Instead of treating unstructured data as isolated pieces of information, Reltio enables organizations to connect relevant insights from diverse sources to existing entity management frameworks. This means that customer concerns noted in call transcripts, obligations hidden in contract amendments, and recurring themes in support communications can all contribute to a unified, governed profile. Importantly, these insights adhere to the same quality controls and governance policies as structured data, making them reusable and timely across systems—from dashboards to AI applications. Furthermore, companies are leveraging advanced search techniques that prioritize meaning over mere keyword matching. This allows AI agents to extract the full narrative from documents, presentations, chats, and images, enhancing their understanding of the information they process. With a technique known as retrieval-augmented generation (RAG), AI can dynamically pull the most relevant data to inform its responses and recommendations, thus recognizing the importance of context. The convergence of structured data and meaning-based search equips AI agents with a stronger foundation to deliver accurate answers and informed actions. As organizations connect more structured and unstructured data, their enterprise information will more accurately reflect real-world operations. The effectiveness of AI-driven solutions hinges on the quality of their underlying data infrastructure. If this foundation lacks access to 80% of relevant information hidden in unstructured formats, investments in AI may yield disappointing returns. The opportunity to unlock this potential is already at hand. Enterprises do not need to seek new data; they must instead focus on how to connect, govern, and leverage existing information. The question remains: will organizations take proactive steps to seize this competitive advantage or wait until integrated data becomes a mere expectation? Reltio offers the tools to help businesses connect fragmented data and provide AI with the necessary context to scale effectively.