The Next Gen AI Engine
Our NLP Engine changes the way businesses use data to make decisions
Natural Language Processing (NLP) and Machine Learning (ML) are the most transformative technologies of our time, and Nowigence is committed to increasing the speed to which users, teams, and businesses make data-driven decisions. We partnered with Orion Business Innovation to deliver complete digital transformation for businesses across the globe.
Pluaris combines search with novel machine learning and natural language processing techniques to deliver decisional boundaries (for each user) and traceable intelligence derived from a rich spectrum of data types and sources, both inside and outside the enterprise. This capability to deliver intelligence on demand from a complex set of disparate sources applies to a wide variety of roles and processes.
Are you using all available data to make the best business decisions? Most companies don’t. International Data Corporation states that only 10% of all data created is in a structured (numeric), analyzable format. This means that 90% of data is unstructured and must either be manually analyzed by expensive human capital, or left out of the decision-making process entirely. This changes once you subscribe to Pluaris.
The human brain has a limited capacity to store and retrieve information. With Pluaris, we extract intelligence from large amounts of data and summarize it into easily consumable content. Whether you create an alert, customize an intelligence briefing, or search for information on-the-fly, Pluaris turns text to context, leaving you with more time for deeper analysis and faster decision-making.
The next generation on-demand, intelligence discovery and exploration augmented by helicon (complex search technique that combines keyword and semantic search) and machine learning (ML) technologies providing two answers. The first one is mined from external and publicly available sources while the second one is a precise answer from internal data sources. Both structured and unstructured content is mined to ensure that intelligence inclusion is complete and traceable.
Institutional Memory (Storage)
Business professionals are required to ingress a lot of content from various data sources. Every job has its own requirements. First, machines help with content retention. Secondly, Pluaris is unique in allowing each user to decide the data that is needed for ones’ daily work needs. The user then controls the flow of intelligence to the team, function or the entire business. Supervised learning including active learning as part of Machine Learning techniques results in valuable insight extraction, auto-filling routine applications, benchmarking, anomaly alerting, instant briefings, answering customer concerns, training new hires and myriads of other uses.
Data needs flexibility in its presentation. Different users require different techniques. Pluaris saves you over 2 hours a day in updating and retrieving the most relevant information. Constant focus and active learning on usage by individuals with data cleansing ensures that your data engine is humming. In-built tools and techniques that allow edits with human interface creates a uniquely designed UI with drill down capabilities from unstructured or structured data. Most BI tools chart out trends using structured data.
Rapid ML Training Algorithms
Subscribe to the off-the-shelf platform to get going from Day-1. Business Leaders are adept in linguistic skills trained to get their messages across to their audience in generic high-school level communication techniques. Nowigence has developed its own unique blend of automated and human assisted techniques for rapid machine learning modules even when data paucity exists.
Pluaris puts the power of AI in your hands
Pluaris delivers personalization at scale, with the flexibility to adjust as your business needs change. Uncover hidden insights for better business decisions. Pluaris is great for any industry or role who need to:
- Comprehend massive amounts of data in seconds
- Gather data on-the-fly
- Be automatically informed of changes in their data
- Fill the knowledge gap between teams
- Improve relevancy, quality, and the capacity of their data
- Harmonize their data across multiple systems
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