Leveraging Unstructured Data for AI
22 days ago
Expert Type *
Expert Type
Expertise *
Other
Legal
Technology/Software & Services
Risk & Compliance
Clearing & Settlement
Research
Communications & Marketing
Consulting
Accounting
Asset Management Solutions
Insurance
Wealth Management Solutions
Professional Services
Industry Categories *
Technology/Software & Services
Legal
Asset Management Solutions
Risk & Compliance
Professional Services
Accounting
Consulting
Insurance
Research
Communications & Marketing
Other
Clearing & Settlement
Wealth Management Solutions
Upload a square image that is approx. 200 x 200 px in size.
Expert Type *
Expert Type
Expertise *
Other
Legal
Technology/Software & Services
Risk & Compliance
Clearing & Settlement
Research
Communications & Marketing
Consulting
Accounting
Asset Management Solutions
Insurance
Wealth Management Solutions
Professional Services
Industry Categories *
Technology/Software & Services
Legal
Asset Management Solutions
Risk & Compliance
Professional Services
Accounting
Consulting
Insurance
Research
Communications & Marketing
Other
Clearing & Settlement
Wealth Management Solutions
Minimum Size 400x400 and Aspect Ratio 1:1
Back
22 days ago
A large financial institution sought to leverage AI to analyze and review
large volumes of unstructured data, such as emails and messages, for
compliance violations and other business risk. However, they had
limitations that prohibited them from implementing AI technology at the
enterprise level. In this case, their AI application was limited to
processing 20,000 messages per day. Additionally, certain types of
information needed to be filtered from analysis.
The financial institution approached ZL Tech for a solution to its big data
problems, ultimately implementing the ZL platform to unify its data
management and search capabilities across the enterprise.