Automate Data Processes with Artificial Intelligence
Using the cognitive engine from the Kingland Platform, we combine decades of data science expertise with cognitive data process automation to create neural network models that learn and improve with each interaction. The engine learns by identifying and using patterns and trends through means such as statistical pattern learning, sentiment analysis, document summarization, and entity relation modeling. From a function perspective, the cognitive engine can:
- Extract or harvest data from many types of documents and sources.
- Automatically classify entities and suggest data results or augmentation.
- Automate exception processing and data stewardship.
- Predicatively determine data cleansing, enrichment, duplication, and maintenance actions.
Additionally, with Kingland, we build and refine a corpus of training data from day one. Using our Data Science and Software Lab in Ames, Iowa, our high-skilled data analysts and cognitive engineers resolve exceptions and produce the training data used by our cognitive engine to improve the decision-making process. The result is increased efficiency quarter over quarter that lowers the overall cost of the solution, without sacrificing data quality.
Cognitive systems, used by many successful firms, are designed to extend what humans and machines can do on their own. These actions move beyond past approaches to accurately find attributes and predictably grade accuracy and confidence. They go well beyond a common application's ability to seek, identify, and extract information from the Internet. The best systems have the ability to understand the nuances of searching for, extracting, and updating relevant information that matches - in context - the most important attributes for reference data.
See how cognitive fits into your existing and future projects.