Semantic Layer Strategy for Linked Data Investigations

A government organization sought to more effectively exploit their breadth of data generated by investigation activity of criminal networks for comprehensive case building and threat trend analysis. EK engaged with the client to develop a strategy and product vision for their semantic solution, paired with foundational semantic data models for meaningful data categorization and linking, architecture designs and tool recommendations for integrating and leveraging graph data, and entitlements designs for adhering to complex security standards. Continue reading

Building a Semantic Enterprise Architecture

The EK Difference Using a hybrid analysis approach, consisting of a combination of user-driven research (facilitated workshops, focus groups, and interviews) and technology-driven research (in-depth analysis of the existing technology), EK captured the current Enterprise Architecture using our Semantic Enterprise … Continue reading

A Semantic Layer to Enable Risk Management at a Multinational Bank

Enterprise Knowledge is working with a multinational bank to enable their risk-assessing processes by using semantics and connected data. Heavily regulated financial services firms require comprehensive and complex risk management. This requires employees to thoroughly account for risk and report it in detail to regulators. Continue reading

Enhancing Retail Performance with Semantic Layer As an Enabler for Data and Analytics Teams

In the fast-paced retail sector, organizations need to be able to quickly view store performance analytics in order to make crucial decisions. A leading global retail chain faced significant delays of up to 5-6 weeks when attempting to retrieve essential store performance metrics and create reports for executive leadership. This bottleneck was largely due to … Continue reading

Women’s Health Foundation – Semantic Classification POC

A humanitarian foundation focusing on women’s health faced a complex problem: determining the highest impact decision points in contraception adoption for specific markets and demographics. Two strategic objectives drove the initiative—first, understanding the multifaceted factors (from product attributes to social influences) that guide women’s contraceptive choices, and second, identifying actionable insights from disparate data sources. The key challenge was integrating internal survey response data with internal investment documents to answer nuanced competency questions such as, “What are the most frequently cited factors when considering a contraceptive method?” and “Which factors most strongly influence adoption or rejection?” This required a system that could not only ingest and organize heterogeneous data but also enable executives to visualize and act upon insights derived from complex cross-document analyses. Continue reading

Natural Language Search on Big Data

The Solution By extracting key entities or metadata fields, such as topic, place, person, customer, plant, etc. from their sample files and data sets, Enterprise Knowledge (EK) developed an ontology to describe the key questions business users were interested in … Continue reading

Humanitarian Foundation – SemanticRAG POC

A humanitarian foundation needed to demonstrate the ability of its Graph Retrieval Augmented Generation (GRAG) system to answer complex, cross-source questions. In particular, the task was to evaluate the impact of foundation investments on strategic goals by synthesizing information from publicly available domain data, internal investment documents, and internal investment data. The challenge laid in …. Continue reading