Access relevant web data feeds through our APIs
Nexis Data as a Service features several APIs for data integration into your trend analysis tools or to power bespoke big data research. Deliver web data feeds featuring current and historical news articles, media monitoring data, PEPs data for risk management, and other alternative data to complement enterprise data.
Nexis DaaS APIs provide access to data with multiple ways of accessing it and flexibility in how it is searched, delivered and hosted.
- Bulk API allows you to subscribe to ATOM, XML-based semi-structured data feeds of news, legal and regulatory content at the publication level—with a data archive reaching back more than 30 years—to deliver a large volume of content for historical analysis, predictive modeling and more.
- The RESTful API offers access to enhanced functions—search, retrieve, saved searches and work folders—within your own user interface, so you can access the full LexisNexis content set and retrieve data on demand.
- Constant call API empowers ongoing monitoring of specific datasets, such as PEPs and watchlists for proactive risk management.
Nexis Data as a Service also offers access to extensive online resources to help you gain in-depth knowledge of various web services calls and codes for variety of development environments.
Why the data wrangler you choose matters
Tap into alternative data sources, unique for their volume and variety, to support data analysis and interpretation for a wide range of financial, corporate, risk, academic and brand database research.
Give your data analysis tools better fuel with smart content enriched with expertly-applied semantic analysis to drive precision search, increased relevance and faster discovery for quantitative and qualitative business data analysis.
Move from data integration to actionable insights by choosing an experienced Data as a Service partner. LexisNexis®, a trusted content aggregator for business and legal organizations for more than 45+ years, pioneered the use of machine learning and data visualization in our applications, decades before their mainstream use.