Data from multiple sources moves through several systems & is transformed, which leads to non-traceability of data’s origins, transformations & errors
Agreements in PDF or non machine-readable format require manual processing to detect non-compliance, which is expensive & difficult to scale; lack of compliance in agreements expose organizations to various risks.
Library of 25+ proprietary supervised & unsupervised algorithms, pre-trained & tested for our products
30+ probabilistic spatial & temporal graph algorithms to determine links & connected entities
Prebuilt financial ontologies & business rules that each product will improve over time
60+ algorithms for cleansing, harmonizing & validating data from internal & external sources in 30+ formats, e.g., JPEG, video, PDFs
40+ scrapers & connectors for ingesting web & paid data subscriptions, e.g., news, social media, traffic, geo-location, sanction lists
In-built reinforcement learning algorithms that improves our products’ performance over time “with & without a human loop”
Pre-built graphical user interface (GUI) & APIs for quick deployment & integration with clients’ workflows
Highly scalable with parallel & distributed computing with options to deploy on-premise or consume as SaaS
40+ proprietary ML & NLP algorithms to identify transformations & business rules and to fix manual & OCR errors
91% – 98% accuracy that improves over time & with high quality ontology
60% – 85% improvement in time & cost over the current manual process
Provides role-based access & sends alerts for exceptions to strategies, policies & compliance guidelines