From Manish Sood, CEO and Founder of Reltio
Approximately 80% of company data is stored in emails, contracts, call logs, and PDFs that cannot be handled by traditional databases. Much of this “unstructured” data is ignored not because it has no value, but because it is difficult to reliably connect to the structured systems that businesses already rely on.
Most companies already have the data they need to make AI work. So why are so many AI efforts underperforming? One of the big problems is that there is too much valuable information outside of the systems on which AI relies.
Emails, contracts, call logs, PDFs, and clinical notes contain important context about customers, suppliers, products, and risks. Unstructured data makes up an estimated 80% of enterprise information, but it rarely makes it into the data layers that feed AI models and automation systems. Not because it’s not valuable, but because it’s difficult to reliably connect, manage, and use it alongside structured data.
As companies rush to deploy AI and agent systems, this missing context has emerged as a significant limitation. Even well-trained AI models can provide incomplete answers if they have limited knowledge or context. Successful organizations will not be those with the “right” AI models or agents, but those that provide AI with a rich, real-time, 360-degree contextual view of the business, including vast amounts of unstructured data.
Rapid growth of unstructured data
The most important business activities take place in human language, not in fields or tables.
People explain, negotiate, document, and interpret in emails, documents, chats, call notes, contracts, reports, and more. Salespeople don’t think in drop-down menus. Lawyers don’t write contracts in neat rows and columns. Customers don’t describe their problems with predefined schemas. All of that context will naturally be unstructured text.
Over the past few decades, organizations have built systems to capture transactional, inventory, and financial data as they move everything to digital systems. These systems are great at recording what happens. However, the reasons, nuances, and intentions were left to free description. Over time, the amount and importance of that narrative layer has exploded, especially as business has become more complex, regulated, and global.
Ironically, the more companies “digitize”, the more unstructured data they generate.
Why this matters now: Context is key
AI has changed economics, but not the fundamentals. Models can read unstructured data, but require clean, connected, and trusted data. context To be helpful. AI models or agents cannot establish connections between unstructured documents and structured databases. Context must be properly delivered and provided to the agent or model. Without timely and reliable context, AI systems will hallucinate, miss nuance, or make decisions in a vacuum.
That’s why the real change isn’t just about analyzing unstructured data. Connect it to an intelligent data layer, where narrative context enriches your enterprise’s structured data and consistently feeds into your AI systems in real-time. Once that happens, unstructured data will no longer be a problem and will provide the context that enterprise AI has been lacking.
Combine unstructured data into intelligent 360-degree profiles
Reltio, a contextual intelligence company, has developed new technology that enables companies to incorporate unstructured data sources into intelligent data graphs to build the most comprehensive 360-degree profile of any entity in an industry today.
Instead of treating emails, documents, and transcripts as standalone artifacts, you can connect relevant information from unstructured sources to entities your business already manages. Customer concerns expressed in call transcripts, supplier obligations buried in contract amendments, or regular feedback in support notes can all be shared and made part of a rich, managed profile.
Importantly, these signals inherit the same quality control, governance, and access policies as structured data. These become reusable and timely contexts that flow throughout your systems, from dashboards and workflows to AI applications.
At the same time, companies are using new kinds of searches that look for meaning, not just keywords, so AI agents can pull out whole stories buried in documents, slide decks, chats, and even images.
Using an approach known as search augmentation generation (RAG), AI “looks at things” in the moment. Instead of forcing everything into strict fields and categories, extract the most relevant files and writing and use that material to answer questions and make recommendations. This is important because a lot of business knowledge relies on nuances, such as the intent behind an email, the context of a contract clause, or the domain language of a technical report.
Real results come when captured content is associated with the right customers, products, suppliers, and other important records. AI not only finds information, but also understands what it means in the context of your business.
In summary, structured data and meaning-based search can give AI agents more accurate answers, clearer explanations, and greater confidence in taking action.
Reltio
The result is a fuller 360-degree profile, as shown in the image above. As more structured and unstructured signals are connected, enterprise data will better reflect how businesses actually operate.
The time to act is now
The AI agents, co-pilots, and intelligent automation that companies are rushing to deploy only work because of the underlying data foundation. Investments in AI will not be as effective if the foundation is missing 80% of relevant information because no one can access the information hidden in emails and documents.
The gold mine is already there. Tools are now available to extract value from it. The question is whether your organization will act while there is still time to gain a competitive advantage, or wait until the competitive window closes when integrated data becomes a critical factor.
Businesses don’t need new data sources. Emails, documents, transcripts, and reports already exist. The change is in how that information is connected, managed, and reused across the organization.
See how Reltio can help Enterprises connect fragmented data and provide AI with the context it needs to perform at scale.
This post was created by Reltio. Insider Studio.
