We have entered a new and exciting era for AI search and retrieval. Advanced AI capabilities are breaking down data and linguistic barriers, allowing organizations to generate more context-rich responses and unlock hidden value across their business — a shift reflected in the rapid growth of the AI knowledge management market, which is projected to surge to $62.4 billion by 2033.

“What I’m really excited about is teaching users that they can expect more from their search. They should ask challenging and specific questions and expect positive results.” – Ben Eagan, Technical Lead, Search at Cohere

Large language models like Cohere Embed 4, are now capable of accurately retrieving information from previously hard-to-access data formats, such as complex PDFs and presentation slides filled with multiple data modalities like diagrams, tables, graphs, and images. Embed 4 can do so across more than 100 languages while being securely, privately deployed, and tailored to specific regulated industry domains, such as healthcare and banking.

The high cost of poor search

Businesses are awash in data more than ever, yet finding the right data and drawing intelligent insights from it remains a serious, costly problem.

One survey this year of 12,000 global knowledge workers found that:

Executives and teams spend a quarter of each week searching for information
56% say they have to ask others or schedule meetings to get answers
A total of 2.4 billion hours is wasted each year searching for information

At the same time, leaders are under pressure to make increasingly complex decisions faster. According to Gartner, 71% of organizations are making more complex decisions than they used to, and more than half say they must make those decisions faster than ever.

Data is often siloed and held in formats ranging from images to text, as well as in multiple languages. The difficulty of accessing and accurately interpreting this “messy” data — which by some estimates accounts for 90% of organizational data and is growing fast — in a timely way means that enterprises have to make critical decisions without knowing the full picture.

The challenge of tapping the right data for quick, accurate answers represents a huge, and at times, invisible tax on productivity.

Deeper, compliance-first AI search

The strict data privacy and compliance rules that affect many regulated industries have long been a barrier to effective enterprise-wide data search. One 2023 report found that companies in healthcare and finance were actively not sharing data to avoid the risk of penalties for non-compliance.

“The cost and complexity associated with managing diverse data across the organization is overwhelming.” – Ralph H. Groce III, former CIO at Wells Fargo

Advances in multimodal AI search with enhancements for security-minded industries have marked a breakthrough in search to tap previously impenetrable forms of data.

Embed 4, for example, is:

Optimized with domain-specific understanding of data from regulated industries, such as finance, healthcare, and manufacturing. This enables it to access and understand highly specialized forms of documents found in each industry, such as a bank’s M&A due diligence files, a healthcare firm’s clinical trial reports, or a manufacturer’s product documents.
Scalable to meet the needs of large organizations, where efficiency innovations are a must. It’s designed to output compressed embeddings, which help organizations to save up to 83% on storage costs while maintaining search accuracy.
Deployable in a virtual private cloud (VPC) or on-premises environment. Embed 4 is better suited for regulated industries that require strict data security.

Advancing agentic AI search

Solutions like Embed 4 are paving the way for more advanced and productive GenAI use cases for business, including unlocking productivity through agentic AI applications — like our secure AI workplace North — that enable knowledge workers to quickly conduct research across any data source, in any language, surfacing answers to the most complex questions in a single step.

Innovations like agentic search, in which an AI agent is deployed to engage in an autonomous, iterative search, can yield richer, more deeply reasoned results.

These advances in secure AI search and retrieval capabilities are no less than a paradigm shift for businesses that rely on timely, accurate, contextual information to stay competitive and compliant. The days of fragmented, frustrating search that barely scratches the surface of their data are giving way to a new era of productivity.

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