AKIN Natural Language Processing API


For more information and licensing inquiries, contactinfo@grappledata.com using a valid company/organization email address.


We invite you to try some of our online demos below. These illustrate the type of results you can expect from AKIN:

Demo 1 - Medical Model

Demo 2 - Intents Model - Get Flight Information (Directives & Inquiries)


AKIN NLP Overview

Inspired by limitations encountered in most modern NLP software, we've built a next-generation platform that takes NLP to a whole new level of intelligence, accuracy, and performance. AKIN NLP can significantly augment and automate key workflows in your business. AKIN was developed to have comprehensive intelligence built-in right from the start, requiring far less time and expertise to configure and implement, making it quick and easy for your business to harness its power in an immediately practical way.

Think about any sort of data or information your business receives, either verbally, or in written form, that your business would like to use, but can’t until a human being has reviewed it. AKIN NLP can help your business with this information, saving significant time and money, normalizing your processes, improving the consistency of your operations, and providing a significant competitive edge, driving your reputation and customer satisfaction skyward.

For many types of businesses a large amount of information is still collected, bound up, and stored in unstructured or semi-structured text. Every year, businesses spend enormous amounts of money attempting to successfully manage and extract value from this data, that frequently require manual efforts enhanced by discovery technology that often feels rudimentary and inadequate.

Additionally, businesses and application developers are looking to create more natural interactions with their information systems for consumers, customers, and their employees. They want the ability for users to be able to write or speak inquiries and directives naturally, and have their information systems understand and be able to process this information. This is no easy task.

The problem is that everyone communicates differently. Individuals express their thoughts, ideas, and concepts in so many different, non-standard, unique, and individualistic ways. Exacerbating the problem, people also make mistakes, or speak different native languages leading to unexpected grammatical structures when they write or speak (speech to text). For example, in a medical domain people may have symptoms or issues they express in different unique ways. Several people might describe the issue of having difficulty breathing in a number of ways:

  • “I have a hard time breathing”
  • “Sometimes it’s painful when I inhale”
  • “I find myself gasping for air”
  • “There are times when I can’t catch my breath”
  • “It hurts to breathe”
  • Etc.

Downstream consuming software systems need to be able to understand those concepts and do things like alert key stakeholders or gather significant data for analysis and research. However, those downstream systems need a standardized representation of these concepts, in this case the symptom we describe above, something like “Difficulty Breathing” or “Labored Respiration”. Having a single representation of this symptom makes it extremely easy for other systems to use this information in a structured way.

AKIN was developed to have intelligence built-in from the start, requiring far less time and expertise to configure, and making it easy to quickly get it working for your business in an immediately practical way, instead of requiring a large team of data scientists and months or years of analysis and training. It is geared more toward the role of a data savy information worker than that of an academic, while still retaining the types of control a data scientist would want.

AKIN doesn't require you to tag up tens of thousands of records in haphazard fashion. Additionally, AKIN was designed to be vastly more transparent than most current Machine Learning models. When AKIN does something unexpected, or is not able to accomplish something, it is much more transparent about the "why", allowing users to quickly make targeted improvements to the model that inspire confidence. Users can see deeper into the internals of the AKIN model to understand what it knows and does not know.

To configure AKIN, you directly feed it knowledge in the form of standardized values of concepts and ideas you want detected and fed to your downstream consuming systems. This is done either through easy to use API functions/methods, or via the Model Manager UI. Additionally, you give it synonymous and related terms for the concepts you define. AKIN uses this knowledge to make smart determinations about the text you want it to analyze. You don't have to spend hours tagging up thousands of records to "train" it in a haphazard, disorganized way. You directly feed it knowledge in an orderly fashion, and you can always see what it knows and what it doesn't know. Then, AKIN uses its sophisticated probabilistic AI to detect concepts and ideas within the text even when there are a lot of variations in the way something is written, such as spelling and grammatical errors.

It is not a trivial task to write software capable of recognizing unique expressions, seeing through the “noise”, and really understanding the meaning of what was expressed. Even the most well-known machine learning algorithms and software today are very easy to fool with just a few small errors or unexpected grammatical structures. It’s also unrealistic to expect your IT department to be able to write software that can be capable of handling every scenario of expression.

What’s needed, is an artificially intelligent (AI) platform and framework that make it extremely easy for business information workers to define and model specific domains of knowledge, ideas, and concepts (entities, sentiments, and intents), and then use that information intelligently to detect those concepts in unstructured text, without the user having to know or predict every possible way those concepts might be expressed. Also, information workers should not be forced to sit and tag or markup thousands and thousands of records in order to "teach" the AI what each of the concepts are. This approach is random and haphazard, making it very difficult to know whether or not every possible scenario has been covered. What is needed, is a straightforward way to directly inject knowledge into a system, and for that system to intelligently USE that knowledge-base on its own without much hand-holding.  This is what AKIN provides.

Examples of Usage Industries & Scenarios

  • Medicine - Augmented Experiences and Research
  • Natural Language Query - Ask questions in everyday language
  • Customer, Partner, and Employee Sentiment
  • Customer Support and CRM Enhancement
  • Product Management - Adapt Quickly to Customer Demands
  • Enterprise Compliance - Intelligent Monitoring
  • Intelligent Search - Search by Idea
  • Surveys & Profiling - Let people write in their own words
  • Law/Discovery & Government

AKIN Natural Language Processing provides unparalleled accuracy and performance allowing your business to effectively extract the value from your unstructured text and natural language queries. There is no need to rely solely on centralized Cloud-Only-Based solutions like Google, Alexa, or Cortana that tie you down to an ecosystem and take your data out of your hands. With AKIN you can host anywhere on-premises, and use any speech to text technology with it, like Dragon Naturally Speaking, and those already freely available on mobile devices.

AKIN has been designed to be super intelligent and high performance, and yet still be very lightweight and efficient. It can even be hosted directly on mobile devices or very lightweight client Virtual Machines.


Usage Examples (Code)

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