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The Agiloft AI Core allows you to extract key terms and clauses = from contracts. You can use a machine learning action to map these values t= o fields in records, as well as to create records for each identified claus= e in a table of your choice. You can also use this feature in conjunction w= ith the Word add-in, but must have the Agiloft KB properly configured first= . The exact setup for these use cases depends on your specific needs and yo= ur current KB configuration. You can use the information here as a starting= point or introduction to the available methods of integrating AI with the = rest of a KB, but be prepared to make adjustments to your own system.
Prerequisites
AI features require the Advanced or Premium edition of Agiloft with the = AI Platform add-on. After you finish Setting Up AI, you need to integrate it with = other tables to make it useful. It's likely you'll need to have several tab= les and fields already available in your system to correctly map the AI inp= uts and output fields.
AI capabilities determine the models you can use with your system. Agilo= ft has an emphasis on models that are used for extracting content from= documents and files, but your choice of model depends on the content = you want to extract. For example, some extract metadata, such as titles and= dates, while other models extract whole clauses. Some models don't extract= data, and instead compare similarities or make classifications.
When it comes to extracting content, there are some limitations. F= or a list of other limitations, visit Limitations of AI.
.docx
files with Agiloft, but=
the model can also extract data from digitally-created and searchable PDFs=
; the model cannot extract data from "image only" or scanned PDFs. It also =
cannot extract data from handwritten documents.Contracts AI is an AI Capability, developed by Agiloft, that consi= sts of two ATHENA models that can extract information about various differe= nt types of contracts.
When you create a machine learning action that uses a model that extract= s data from the contract document, such as either ATHENA model, you can pic= k and choose which data actually gets extracted and which data you want the= model to ignore. You can make these decisions from the Labels ta= b of the machine learning action wizard, as long as the model you've s= elected contains a label set (see step 8 in Extracting Content checklist in= the previous section). If your model does not contain at least one label s= et, the Labels tab does not appear. If either ATHENA model is selected, the= Labels tab is visible contains labels for generic data that is common= ly used throughout many kinds of contract types, as well as specialize= d labels for data used in specific contract types. In the example below, yo= u can see that ATHENA-CE-AS has generic labels for clause data such as Assi= gnment and Contract Title, as well as labels for specialized or contact-spe= cific clauses, such as Closing Adjustments for an Asset Purchase Agreement.=
Although some ATHENA labels may only be relevant when analyzing&nbs= p;specific contract types, the generic labels can be used with virtually an= y kind of contract as long as the document format does not drastically stra= y from the standard. Currently, there are many different contract types and= labels directly supported by the ATHENA models.
You can also use AI to extract clauses and = key terms from Microsoft Word documents directly using the Agiloft Add-in f= or Microsoft Word. The add-in uses preconfigured Machine Learning actions t= o extract clauses and metadata from the Word document, which can then be ed= ited and added to your KB as records. You can select which action buttons t= o use for the Word add-in in the Word Add-in Integration wizard. For more i= nformation about the Word add-in, visit Agiloft Contract Assistant for Word.