The toughest data for AI to understand is unstructured data with no metadata tags. Manual deployment of manpower will take a long turnaround time - the average person can read 200 words per minute and has an attention span of 10-20 minutes. Extended demands of human attention would lead to human error and fatigue. The way the human mind is structured is to search through keywords in a dataset, but even the best combination of keywords can lead to missed information and opportunities. Yet our AI engine, that is commercially proven in multiple deployments overcomes these problems by automating the process in an error-free way by scanning millions of words in minutes through a contextual engine. The AI employs NLP techniques to process large amounts of text too unwieldy for any person or team to process. The AI does not tire and because of machine learning, actually performs better as the volume of processed text increases. Our AI is also adept at fully recognising the Romanised Asian names of people and companies far better than other NLP solutions. The technology save days of effort and renders previously impossible tasks, possible.
Artificial Intelligence capable of:
Contextual and linguistics analysis
Entity and relationship extraction
Tabular and parametric data harvesting
Natural Language Processing
Unique advantage of having access to complete official corporate registry databases, allowing NLP ML AI to fully recognize Asian names of people and companies far better than other NLP solutions.
News Scanning is perfect for: Fund Managers & Creditors, Law Enforcement, Intelligence Analysts
Real-time customer feedback monitoring is perfect for: Hotels, Mall operators, Airports & Train Operators
Document Discovery is perfect for: Law Firms, Auditors, Investment Firms, Regulators, Law Enforcement
Any custom application of AI required for text based processing.
Real life applications include the monitoring of global websites and news; processing volumes of customer feedback; extracting knowledge from emails (for example, scanning for allusions to collusion or corruption); the categorization of terabytes of in-house documents for document discovery and precedence searching; and the custom application of ingesting and sorting any data the organization may receive daily such as financial market news, news-feed APIs, etc.
The market trend works towards automation, AI augmented work environements so that employees can focus on strategic information and act swiftly on actionable information instead of being bogged down with menial work.
AI is increasingly deployed in tasks that require a degree of privacy or secrecy and one leg of a security leak is closed.
AI can be deployed round the clock hence the efficiency is increased; in addition, machine learning ensures that when work volume is increased, the AI gets better at its task instead of increased error when a human is deployed.
The value of a mature AI that can be deployed has come down to a cost where it may make sense for a medium enterprise to deploy this solution to turn the AI inwards towards its data or outwards to ingest, hence the market is increasing for on premise deployments.
A Natural Language Processing, Machine Learning AI, especially a mature one with years of data processing and the right contextual approach by the provenance of its creators, has ensured the efficiency in contextual understanding that makes deployment feasible for replacing human man-hours.
The increased efficiency will lead to improved response time, reduced errors, and privacy in operation so that humans can make decisions quickly and on a more strategic level, or freed from menial error-prone work.