Example: You have chat data and you want to identify the most popular topics from all conversations, extract email addresses and phone numbers, and determine if a topic was discussed in a positive, neutral or negative manner.
Via our point and click Workflow builder, you would add a Topic and Sentiment model and parser objects. You upload your texts to schedule a job; which passes the data to the Workflow.
AiModelBuilder creates various files; which are all related to your key and our system generated keys to support offline analysis.
If you were using any other service, that would be a minimum of two API calls, each requiring custom coding to reach the different API services and custom models for each, not to mention the time invloved in building those models. And then your development team would need to code a system to parse the results and then create a data design to keep all the results related for offline analysis.
AiModelBuilder does all of the above, without any coding!
An AiModelBuilder Workflow can link models and parsers to solve one need today, and gives you the ability to change it up tommorrow to solve another business need, without any coding! Try it today!
When building a Custom Extractor, big tech companies will have you tag every occurence of text you wish to extract from your corpus when building an Extraction Model, also known as Named Entity Recognition. When you have 15,000 sentences to wade through, this could take quite some time, not to mention the staffing costs. We took a different approach. Imagine you have 20 texts you would like to extract. Simply search for the first occurence and tag it. Repeat for the other 19. You're done! AiModelBuilder automatically locates every occurence before it trains the model, saving you an immense amount of time, and money! Results? Today!
Each plan includes a Parser Library. Select form an assortment of common Regular Expression patterns. To protect customer privacy in processed results, select a Redact method. Set any Regular Expression to replace texts with either a Label or a Token! AiModelBuilder returns the original sentence, the redacted version, and also identifies which items were replaced and the related label or token in the same result! Simply store the undredacted version in a secure datastore, and release the redacted version to your computer geeks or data scientists to support there data analysis. No Coding, No Apis, just a few clicks. Results? Today!
Processing of your data generates various results. Each includes system generated unique identifiers that are linked to your row id. Some results will output two files, where one includes many items extracted from a sentence, and the other a list of the sentences (one to many relationship). Where a row of text has multiple sentences as determined by our sentence parser model, the system generates a key for each. All results from the different models you include in a Workflow include the same sentence identifier, allowing you to link all the results and potentially to other tables in your database via your unique key.
Select from an assortment of Regular Expresssions to parse texts. A Regular Expression identifies a pattern in texts. For example, you could extract emails, phone numbers, credit card numbers, social insurance numbers, file names, hashtags, postal/zip codes and so much more. Add them to a Workflow as a Task. When patterns are identified, AiModelBuilder extracts texts. No Coding, No APIs! Yes we took care of that. Regular Expressions tested, and ready to do parse, today!
Topic Extractor, Parts of Speech, Sentiment Models for Products, Movies and Restaurants. Myers Briggs and Big5 Personality Models, Spam, Profanity, Urgency, Dates, Organizations, Persons and so much more. Include one or more in a Workflow today! Super simple setup. Simply add them to your Dashboard via the Explore Models pick list. Then add them to a Workflow via a click here and there. Select the Topic and a Sentiment model to identify product of service strengths or weaknesses from chat data or feedback. Results with a Positive Sentiment identify strengths. Identify specific issues via results returned form the Topic model. And did I mention, these are the Free Models. Results? Today!