Natural Language Processing Applications

We have been developing cutting edge AI applications leveraging natural language processing (NLP) to solve some longstanding data quality and data analysis problems for our customers in the aerospace and defense industry. These NLP innovations can be integrated into production applications to greatly improve both the user experience and data quality at the point of entry. The most advanced use cases have been equipment maintenance data entry applications.

The opportunity to leverage AI NLP can be summarized as follows:

Enterprise IT systems can be incrementally upgraded with NLP driven microservices to improve enterprise system user experience with “smart” features and improve user productivity with automations and advanced features
Upgrades and add new features powered by data & AI/ML
Data processes can be automated at scale leveraging the latest tools and tech
Leverage enterprise level investment in foundational data platforms
Build next generation data pipelines and data driven applications & AI/ML
Leverage the latest data tools and infrastructure for organizational value

Organizations often have vast amounts of unused data, resembling an iceberg where only a small portion is visible (used) while the majority remains untapped beneath the surface. Many organizations don’t even know they have this data, what is there, or how it can be used. Tapping into this data is integral to business performance and insights within an organization, thereby unlocking value.

Natural Language Processing (NLP)

NLP is a machine learning technology that gives computers the ability to interpret, manipulate, and comprehend human language. NLP enables powerful new solutions for text and human interaction.

NLP is a powerful technology that is playing a growing role in enterprise solutions that help streamline and automate business operations, increase employee productivity, and simplify mission-critical business processes.

NLP Use Cases:

Data Migration: Matches narrative text fields to map data fields
Data cleansing: Identifies incomplete or incorrect data in the data source
Data classification: Using historical data patterns, systems are trained to categorize data into predefined classes or labels.
Data retrieval / search: find other records that have a similar meaning to the search term
Standardize data entry fields
Summarize text or data records

Our NLP Capabilities:

Data engineering – preparing data for data science and AI/ML ops
Natural language processing (NLP) – custom solutions/microservices

We can integrate new capabilities into enterprise systems with data driven microservices. We can build data engineering & data transformation pipelines using cutting edge tools such as Databricks.
We have experience with Air Force maintenance and product data (e.g. FMxC2 /G081, REMIS, BLADE).
Our service is complementary to IT and general software engineering functions.